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+<li><a class="dropdown-item" href="https://amr-for-r.org/articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
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+    <li><a class="dropdown-item" href="https://amr-for-r.org/articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
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@@ -7,7 +7,7 @@
 
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-    <li><a class="dropdown-item" href="articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="articles/AMR_with_tidymodels.html"><span class="fa fa-square-root-variable"></span> Use AMR for Predictive Modelling (tidymodels)</a></li>
     <li><a class="dropdown-item" href="articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
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     <li><a class="dropdown-item" href="articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
-    <li><a class="dropdown-item" href="articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="reference/mdro.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
     <li><a class="dropdown-item" href="articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
-    <li><a class="dropdown-item" href="articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply EUCAST Rules</a></li>
     <li><a class="dropdown-item" href="reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
     <li><a class="dropdown-item" href="reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
     <li><a class="dropdown-item" href="reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
@@ -33,8 +33,10 @@
 <li class="nav-item"><a class="nav-link" href="articles/AMR_for_Python.html"><span class="fa fab fa-python"></span> AMR for Python</a></li>
 <li class="nav-item"><a class="nav-link" href="reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
 <li class="nav-item"><a class="nav-link" href="authors.html"><span class="fa fa-users"></span> Authors</a></li>
-      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
-<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
+ <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item"><a class="nav-link" href="news/index.html"><span class="fa fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fa-github"></span> Source Code</a></li>
       </ul></div>
 
 
@@ -304,7 +306,7 @@ END OF TERMS AND CONDITIONS
 </div>
 
 <div class="pkgdown-footer-right">
-  <p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/assets/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/assets/logo_umcg.svg" style="max-width: 150px;"></a></p>
+  <p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://amr-for-r.org/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://amr-for-r.org/logo_umcg.svg" style="max-width: 150px;"></a></p>
 </div>
 
     </footer></div>

articles/AMR_for_Python.html

@@ -6,20 +6,21 @@
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 <title>AMR for Python • AMR (for R)</title>
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@@ -29,7 +30,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9099</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9033</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -43,13 +44,13 @@
   <ul class="dropdown-menu" aria-labelledby="dropdown-how-to">
 <li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
     <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
-    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/AMR_with_tidymodels.html"><span class="fa fa-square-root-variable"></span> Use AMR for Predictive Modelling (tidymodels)</a></li>
     <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
     <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
     <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
-    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../reference/mdro.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
     <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
-    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply EUCAST Rules</a></li>
     <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
     <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
     <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
@@ -60,8 +61,11 @@
 <li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
       </ul>
 <ul class="navbar-nav">
-<li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
-<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
+<li class="nav-item"><form class="form-inline" role="search">
+ <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json">
+</form></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fa-github"></span> Source Code</a></li>
       </ul>
 </div>
 
@@ -91,37 +95,50 @@ antimicrobial resistance (AMR) analysis. It provides extensive features
 for handling microbial and antimicrobial data. However, for those who
 work primarily in Python, we now have a more intuitive option available:
 the <a href="https://pypi.org/project/AMR/" class="external-link"><code>AMR</code> Python
-Package Index</a>.</p>
-<p>This Python package is a wrapper round the <code>AMR</code> R
+package</a>.</p>
+<p>This Python package is a wrapper around the <code>AMR</code> R
 package. It uses the <code>rpy2</code> package internally. Despite the
 need to have R installed, Python users can now easily work with AMR data
 directly through Python code.</p>
 </div>
 <div class="section level2">
-<h2 id="install">Install<a class="anchor" aria-label="anchor" href="#install"></a>
+<h2 id="prerequisites">Prerequisites<a class="anchor" aria-label="anchor" href="#prerequisites"></a>
+</h2>
+<p>This package was only tested with a <a href="https://docs.python.org/3/library/venv.html" class="external-link">virtual environment
+(venv)</a>. You can set up such an environment by running:</p>
+<div class="sourceCode" id="cb1"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" tabindex="-1"></a><span class="co"># linux and macOS:</span></span>
+<span id="cb1-2"><a href="#cb1-2" tabindex="-1"></a>python <span class="op">-</span>m venv <span class="op">/</span>path<span class="op">/</span>to<span class="op">/</span>new<span class="op">/</span>virtual<span class="op">/</span>environment</span>
+<span id="cb1-3"><a href="#cb1-3" tabindex="-1"></a></span>
+<span id="cb1-4"><a href="#cb1-4" tabindex="-1"></a><span class="co"># Windows:</span></span>
+<span id="cb1-5"><a href="#cb1-5" tabindex="-1"></a>python <span class="op">-</span>m venv C:\path\to\new\virtual\environment</span></code></pre></div>
+<p>Then you can <a href="https://docs.python.org/3/library/venv.html#how-venvs-work" class="external-link">activate
+the environment</a>, after which the venv is ready to work with.</p>
+</div>
+<div class="section level2">
+<h2 id="install-amr">Install AMR<a class="anchor" aria-label="anchor" href="#install-amr"></a>
 </h2>
 <ol style="list-style-type: decimal">
 <li>
-<p>First make sure you have R installed. There is <strong>no need to
+<p>Since the Python package is available on the official <a href="https://pypi.org/project/AMR/" class="external-link">Python Package Index</a>, you can
+just run:</p>
+<div class="sourceCode" id="cb2"><pre class="sourceCode bash"><code class="sourceCode bash"><span id="cb2-1"><a href="#cb2-1" tabindex="-1"></a><span class="ex">pip</span> install AMR</span></code></pre></div>
+</li>
+<li>
+<p>Make sure you have R installed. There is <strong>no need to
 install the <code>AMR</code> R package</strong>, as it will be installed
 automatically.</p>
 <p>For Linux:</p>
-<div class="sourceCode" id="cb1"><pre class="sourceCode bash"><code class="sourceCode bash"><span id="cb1-1"><a href="#cb1-1" tabindex="-1"></a><span class="co"># Ubuntu / Debian</span></span>
-<span id="cb1-2"><a href="#cb1-2" tabindex="-1"></a><span class="fu">sudo</span> apt install r-base</span>
-<span id="cb1-3"><a href="#cb1-3" tabindex="-1"></a><span class="co"># Fedora:</span></span>
-<span id="cb1-4"><a href="#cb1-4" tabindex="-1"></a><span class="fu">sudo</span> dnf install R</span>
-<span id="cb1-5"><a href="#cb1-5" tabindex="-1"></a><span class="co"># CentOS/RHEL</span></span>
-<span id="cb1-6"><a href="#cb1-6" tabindex="-1"></a><span class="fu">sudo</span> yum install R</span></code></pre></div>
+<div class="sourceCode" id="cb3"><pre class="sourceCode bash"><code class="sourceCode bash"><span id="cb3-1"><a href="#cb3-1" tabindex="-1"></a><span class="co"># Ubuntu / Debian</span></span>
+<span id="cb3-2"><a href="#cb3-2" tabindex="-1"></a><span class="fu">sudo</span> apt install r-base</span>
+<span id="cb3-3"><a href="#cb3-3" tabindex="-1"></a><span class="co"># Fedora:</span></span>
+<span id="cb3-4"><a href="#cb3-4" tabindex="-1"></a><span class="fu">sudo</span> dnf install R</span>
+<span id="cb3-5"><a href="#cb3-5" tabindex="-1"></a><span class="co"># CentOS/RHEL</span></span>
+<span id="cb3-6"><a href="#cb3-6" tabindex="-1"></a><span class="fu">sudo</span> yum install R</span></code></pre></div>
 <p>For macOS (using <a href="https://brew.sh" class="external-link">Homebrew</a>):</p>
-<div class="sourceCode" id="cb2"><pre class="sourceCode bash"><code class="sourceCode bash"><span id="cb2-1"><a href="#cb2-1" tabindex="-1"></a><span class="ex">brew</span> install r</span></code></pre></div>
+<div class="sourceCode" id="cb4"><pre class="sourceCode bash"><code class="sourceCode bash"><span id="cb4-1"><a href="#cb4-1" tabindex="-1"></a><span class="ex">brew</span> install r</span></code></pre></div>
 <p>For Windows, visit the <a href="https://cran.r-project.org" class="external-link">CRAN
 download page</a> to download and install R.</p>
 </li>
-<li>
-<p>Since the Python package is available on the official <a href="https://pypi.org/project/AMR/" class="external-link">Python Package Index</a>, you can
-just run:</p>
-<div class="sourceCode" id="cb3"><pre class="sourceCode bash"><code class="sourceCode bash"><span id="cb3-1"><a href="#cb3-1" tabindex="-1"></a><span class="ex">pip</span> install AMR</span></code></pre></div>
-</li>
 </ol>
 </div>
 <div class="section level2">
@@ -132,22 +149,22 @@ just run:</p>
 </h3>
 <p>Here’s an example that demonstrates how to clean microorganism and
 drug names using the <code>AMR</code> Python package:</p>
-<div class="sourceCode" id="cb4"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1" tabindex="-1"></a><span class="im">import</span> pandas <span class="im">as</span> pd</span>
-<span id="cb4-2"><a href="#cb4-2" tabindex="-1"></a><span class="im">import</span> AMR</span>
-<span id="cb4-3"><a href="#cb4-3" tabindex="-1"></a></span>
-<span id="cb4-4"><a href="#cb4-4" tabindex="-1"></a><span class="co"># Sample data</span></span>
-<span id="cb4-5"><a href="#cb4-5" tabindex="-1"></a>data <span class="op">=</span> {</span>
-<span id="cb4-6"><a href="#cb4-6" tabindex="-1"></a>    <span class="st">"MOs"</span>: [<span class="st">'E. coli'</span>, <span class="st">'ESCCOL'</span>, <span class="st">'esco'</span>, <span class="st">'Esche coli'</span>],</span>
-<span id="cb4-7"><a href="#cb4-7" tabindex="-1"></a>    <span class="st">"Drug"</span>: [<span class="st">'Cipro'</span>, <span class="st">'CIP'</span>, <span class="st">'J01MA02'</span>, <span class="st">'Ciproxin'</span>]</span>
-<span id="cb4-8"><a href="#cb4-8" tabindex="-1"></a>}</span>
-<span id="cb4-9"><a href="#cb4-9" tabindex="-1"></a>df <span class="op">=</span> pd.DataFrame(data)</span>
-<span id="cb4-10"><a href="#cb4-10" tabindex="-1"></a></span>
-<span id="cb4-11"><a href="#cb4-11" tabindex="-1"></a><span class="co"># Use AMR functions to clean microorganism and drug names</span></span>
-<span id="cb4-12"><a href="#cb4-12" tabindex="-1"></a>df[<span class="st">'MO_clean'</span>] <span class="op">=</span> AMR.mo_name(df[<span class="st">'MOs'</span>])</span>
-<span id="cb4-13"><a href="#cb4-13" tabindex="-1"></a>df[<span class="st">'Drug_clean'</span>] <span class="op">=</span> AMR.ab_name(df[<span class="st">'Drug'</span>])</span>
-<span id="cb4-14"><a href="#cb4-14" tabindex="-1"></a></span>
-<span id="cb4-15"><a href="#cb4-15" tabindex="-1"></a><span class="co"># Display the results</span></span>
-<span id="cb4-16"><a href="#cb4-16" tabindex="-1"></a><span class="bu">print</span>(df)</span></code></pre></div>
+<div class="sourceCode" id="cb5"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb5-1"><a href="#cb5-1" tabindex="-1"></a><span class="im">import</span> pandas <span class="im">as</span> pd</span>
+<span id="cb5-2"><a href="#cb5-2" tabindex="-1"></a><span class="im">import</span> AMR</span>
+<span id="cb5-3"><a href="#cb5-3" tabindex="-1"></a></span>
+<span id="cb5-4"><a href="#cb5-4" tabindex="-1"></a><span class="co"># Sample data</span></span>
+<span id="cb5-5"><a href="#cb5-5" tabindex="-1"></a>data <span class="op">=</span> {</span>
+<span id="cb5-6"><a href="#cb5-6" tabindex="-1"></a>    <span class="st">"MOs"</span>: [<span class="st">'E. coli'</span>, <span class="st">'ESCCOL'</span>, <span class="st">'esco'</span>, <span class="st">'Esche coli'</span>],</span>
+<span id="cb5-7"><a href="#cb5-7" tabindex="-1"></a>    <span class="st">"Drug"</span>: [<span class="st">'Cipro'</span>, <span class="st">'CIP'</span>, <span class="st">'J01MA02'</span>, <span class="st">'Ciproxin'</span>]</span>
+<span id="cb5-8"><a href="#cb5-8" tabindex="-1"></a>}</span>
+<span id="cb5-9"><a href="#cb5-9" tabindex="-1"></a>df <span class="op">=</span> pd.DataFrame(data)</span>
+<span id="cb5-10"><a href="#cb5-10" tabindex="-1"></a></span>
+<span id="cb5-11"><a href="#cb5-11" tabindex="-1"></a><span class="co"># Use AMR functions to clean microorganism and drug names</span></span>
+<span id="cb5-12"><a href="#cb5-12" tabindex="-1"></a>df[<span class="st">'MO_clean'</span>] <span class="op">=</span> AMR.mo_name(df[<span class="st">'MOs'</span>])</span>
+<span id="cb5-13"><a href="#cb5-13" tabindex="-1"></a>df[<span class="st">'Drug_clean'</span>] <span class="op">=</span> AMR.ab_name(df[<span class="st">'Drug'</span>])</span>
+<span id="cb5-14"><a href="#cb5-14" tabindex="-1"></a></span>
+<span id="cb5-15"><a href="#cb5-15" tabindex="-1"></a><span class="co"># Display the results</span></span>
+<span id="cb5-16"><a href="#cb5-16" tabindex="-1"></a><span class="bu">print</span>(df)</span></code></pre></div>
 <table class="table">
 <thead><tr class="header">
 <th>MOs</th>
@@ -199,14 +216,137 @@ the standard name, “Ciprofloxacin”.</p></li>
 </div>
 </div>
 <div class="section level3">
+<h3 id="calculating-amr">Calculating AMR<a class="anchor" aria-label="anchor" href="#calculating-amr"></a>
+</h3>
+<div class="sourceCode" id="cb6"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" tabindex="-1"></a><span class="im">import</span> AMR</span>
+<span id="cb6-2"><a href="#cb6-2" tabindex="-1"></a><span class="im">import</span> pandas <span class="im">as</span> pd</span>
+<span id="cb6-3"><a href="#cb6-3" tabindex="-1"></a></span>
+<span id="cb6-4"><a href="#cb6-4" tabindex="-1"></a>df <span class="op">=</span> AMR.example_isolates</span>
+<span id="cb6-5"><a href="#cb6-5" tabindex="-1"></a>result <span class="op">=</span> AMR.resistance(df[<span class="st">"AMX"</span>])</span>
+<span id="cb6-6"><a href="#cb6-6" tabindex="-1"></a><span class="bu">print</span>(result)</span></code></pre></div>
+<pre><code>[0.59555556]</code></pre>
+</div>
+<div class="section level3">
+<h3 id="generating-antibiograms">Generating Antibiograms<a class="anchor" aria-label="anchor" href="#generating-antibiograms"></a>
+</h3>
+<p>One of the core functions of the <code>AMR</code> package is
+generating an antibiogram, a table that summarises the antimicrobial
+susceptibility of bacterial isolates. Here’s how you can generate an
+antibiogram from Python:</p>
+<div class="sourceCode" id="cb8"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb8-1"><a href="#cb8-1" tabindex="-1"></a>result2a <span class="op">=</span> AMR.antibiogram(df[[<span class="st">"mo"</span>, <span class="st">"AMX"</span>, <span class="st">"CIP"</span>, <span class="st">"TZP"</span>]])</span>
+<span id="cb8-2"><a href="#cb8-2" tabindex="-1"></a><span class="bu">print</span>(result2a)</span></code></pre></div>
+<table class="table">
+<colgroup>
+<col width="22%">
+<col width="22%">
+<col width="22%">
+<col width="33%">
+</colgroup>
+<thead><tr class="header">
+<th>Pathogen</th>
+<th>Amoxicillin</th>
+<th>Ciprofloxacin</th>
+<th>Piperacillin/tazobactam</th>
+</tr></thead>
+<tbody>
+<tr class="odd">
+<td>CoNS</td>
+<td>7% (10/142)</td>
+<td>73% (183/252)</td>
+<td>30% (10/33)</td>
+</tr>
+<tr class="even">
+<td>E. coli</td>
+<td>50% (196/392)</td>
+<td>88% (399/456)</td>
+<td>94% (393/416)</td>
+</tr>
+<tr class="odd">
+<td>K. pneumoniae</td>
+<td>0% (0/58)</td>
+<td>96% (53/55)</td>
+<td>89% (47/53)</td>
+</tr>
+<tr class="even">
+<td>P. aeruginosa</td>
+<td>0% (0/30)</td>
+<td>100% (30/30)</td>
+<td>None</td>
+</tr>
+<tr class="odd">
+<td>P. mirabilis</td>
+<td>None</td>
+<td>94% (34/36)</td>
+<td>None</td>
+</tr>
+<tr class="even">
+<td>S. aureus</td>
+<td>6% (8/131)</td>
+<td>90% (171/191)</td>
+<td>None</td>
+</tr>
+<tr class="odd">
+<td>S. epidermidis</td>
+<td>1% (1/91)</td>
+<td>64% (87/136)</td>
+<td>None</td>
+</tr>
+<tr class="even">
+<td>S. hominis</td>
+<td>None</td>
+<td>80% (56/70)</td>
+<td>None</td>
+</tr>
+<tr class="odd">
+<td>S. pneumoniae</td>
+<td>100% (112/112)</td>
+<td>None</td>
+<td>100% (112/112)</td>
+</tr>
+</tbody>
+</table>
+<div class="sourceCode" id="cb9"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb9-1"><a href="#cb9-1" tabindex="-1"></a>result2b <span class="op">=</span> AMR.antibiogram(df[[<span class="st">"mo"</span>, <span class="st">"AMX"</span>, <span class="st">"CIP"</span>, <span class="st">"TZP"</span>]], mo_transform <span class="op">=</span> <span class="st">"gramstain"</span>)</span>
+<span id="cb9-2"><a href="#cb9-2" tabindex="-1"></a><span class="bu">print</span>(result2b)</span></code></pre></div>
+<table class="table">
+<colgroup>
+<col width="20%">
+<col width="22%">
+<col width="23%">
+<col width="33%">
+</colgroup>
+<thead><tr class="header">
+<th>Pathogen</th>
+<th>Amoxicillin</th>
+<th>Ciprofloxacin</th>
+<th>Piperacillin/tazobactam</th>
+</tr></thead>
+<tbody>
+<tr class="odd">
+<td>Gram-negative</td>
+<td>36% (226/631)</td>
+<td>91% (621/684)</td>
+<td>88% (565/641)</td>
+</tr>
+<tr class="even">
+<td>Gram-positive</td>
+<td>43% (305/703)</td>
+<td>77% (560/724)</td>
+<td>86% (296/345)</td>
+</tr>
+</tbody>
+</table>
+<p>In this example, we generate an antibiogram by selecting various
+antibiotics.</p>
+</div>
+<div class="section level3">
 <h3 id="taxonomic-data-sets-now-in-python">Taxonomic Data Sets Now in Python!<a class="anchor" aria-label="anchor" href="#taxonomic-data-sets-now-in-python"></a>
 </h3>
 <p>As a Python user, you might like that the most important data sets of
 the <code>AMR</code> R package, <code>microorganisms</code>,
-<code>antibiotics</code>, <code>clinical_breakpoints</code>, and
+<code>antimicrobials</code>, <code>clinical_breakpoints</code>, and
 <code>example_isolates</code>, are now available as regular Python data
 frames:</p>
-<div class="sourceCode" id="cb5"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb5-1"><a href="#cb5-1" tabindex="-1"></a>AMR.microorganisms</span></code></pre></div>
+<div class="sourceCode" id="cb10"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb10-1"><a href="#cb10-1" tabindex="-1"></a>AMR.microorganisms</span></code></pre></div>
 <table class="table">
 <colgroup>
 <col width="11%">
@@ -341,7 +481,7 @@ frames:</p>
 </tr>
 </tbody>
 </table>
-<div class="sourceCode" id="cb6"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" tabindex="-1"></a>AMR.antibiotics</span></code></pre></div>
+<div class="sourceCode" id="cb11"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb11-1"><a href="#cb11-1" tabindex="-1"></a>AMR.antimicrobials</span></code></pre></div>
 <table style="width:100%;" class="table">
 <colgroup>
 <col width="4%">
@@ -477,129 +617,6 @@ frames:</p>
 </tbody>
 </table>
 </div>
-<div class="section level3">
-<h3 id="calculating-amr">Calculating AMR<a class="anchor" aria-label="anchor" href="#calculating-amr"></a>
-</h3>
-<div class="sourceCode" id="cb7"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb7-1"><a href="#cb7-1" tabindex="-1"></a><span class="im">import</span> AMR</span>
-<span id="cb7-2"><a href="#cb7-2" tabindex="-1"></a><span class="im">import</span> pandas <span class="im">as</span> pd</span>
-<span id="cb7-3"><a href="#cb7-3" tabindex="-1"></a></span>
-<span id="cb7-4"><a href="#cb7-4" tabindex="-1"></a>df <span class="op">=</span> AMR.example_isolates</span>
-<span id="cb7-5"><a href="#cb7-5" tabindex="-1"></a>result <span class="op">=</span> AMR.resistance(df[<span class="st">"AMX"</span>])</span>
-<span id="cb7-6"><a href="#cb7-6" tabindex="-1"></a><span class="bu">print</span>(result)</span></code></pre></div>
-<pre><code>[0.59555556]</code></pre>
-</div>
-<div class="section level3">
-<h3 id="generating-antibiograms">Generating Antibiograms<a class="anchor" aria-label="anchor" href="#generating-antibiograms"></a>
-</h3>
-<p>One of the core functions of the <code>AMR</code> package is
-generating an antibiogram, a table that summarises the antimicrobial
-susceptibility of bacterial isolates. Here’s how you can generate an
-antibiogram from Python:</p>
-<div class="sourceCode" id="cb9"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb9-1"><a href="#cb9-1" tabindex="-1"></a>result2a <span class="op">=</span> AMR.antibiogram(df[[<span class="st">"mo"</span>, <span class="st">"AMX"</span>, <span class="st">"CIP"</span>, <span class="st">"TZP"</span>]])</span>
-<span id="cb9-2"><a href="#cb9-2" tabindex="-1"></a><span class="bu">print</span>(result2a)</span></code></pre></div>
-<table class="table">
-<colgroup>
-<col width="22%">
-<col width="22%">
-<col width="22%">
-<col width="33%">
-</colgroup>
-<thead><tr class="header">
-<th>Pathogen</th>
-<th>Amoxicillin</th>
-<th>Ciprofloxacin</th>
-<th>Piperacillin/tazobactam</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td>CoNS</td>
-<td>7% (10/142)</td>
-<td>73% (183/252)</td>
-<td>30% (10/33)</td>
-</tr>
-<tr class="even">
-<td>E. coli</td>
-<td>50% (196/392)</td>
-<td>88% (399/456)</td>
-<td>94% (393/416)</td>
-</tr>
-<tr class="odd">
-<td>K. pneumoniae</td>
-<td>0% (0/58)</td>
-<td>96% (53/55)</td>
-<td>89% (47/53)</td>
-</tr>
-<tr class="even">
-<td>P. aeruginosa</td>
-<td>0% (0/30)</td>
-<td>100% (30/30)</td>
-<td>None</td>
-</tr>
-<tr class="odd">
-<td>P. mirabilis</td>
-<td>None</td>
-<td>94% (34/36)</td>
-<td>None</td>
-</tr>
-<tr class="even">
-<td>S. aureus</td>
-<td>6% (8/131)</td>
-<td>90% (171/191)</td>
-<td>None</td>
-</tr>
-<tr class="odd">
-<td>S. epidermidis</td>
-<td>1% (1/91)</td>
-<td>64% (87/136)</td>
-<td>None</td>
-</tr>
-<tr class="even">
-<td>S. hominis</td>
-<td>None</td>
-<td>80% (56/70)</td>
-<td>None</td>
-</tr>
-<tr class="odd">
-<td>S. pneumoniae</td>
-<td>100% (112/112)</td>
-<td>None</td>
-<td>100% (112/112)</td>
-</tr>
-</tbody>
-</table>
-<div class="sourceCode" id="cb10"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb10-1"><a href="#cb10-1" tabindex="-1"></a>result2b <span class="op">=</span> AMR.antibiogram(df[[<span class="st">"mo"</span>, <span class="st">"AMX"</span>, <span class="st">"CIP"</span>, <span class="st">"TZP"</span>]], mo_transform <span class="op">=</span> <span class="st">"gramstain"</span>)</span>
-<span id="cb10-2"><a href="#cb10-2" tabindex="-1"></a><span class="bu">print</span>(result2b)</span></code></pre></div>
-<table class="table">
-<colgroup>
-<col width="20%">
-<col width="22%">
-<col width="23%">
-<col width="33%">
-</colgroup>
-<thead><tr class="header">
-<th>Pathogen</th>
-<th>Amoxicillin</th>
-<th>Ciprofloxacin</th>
-<th>Piperacillin/tazobactam</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td>Gram-negative</td>
-<td>36% (226/631)</td>
-<td>91% (621/684)</td>
-<td>88% (565/641)</td>
-</tr>
-<tr class="even">
-<td>Gram-positive</td>
-<td>43% (305/703)</td>
-<td>77% (560/724)</td>
-<td>86% (296/345)</td>
-</tr>
-</tbody>
-</table>
-<p>In this example, we generate an antibiogram by selecting various
-antibiotics.</p>
-</div>
 </div>
 <div class="section level2">
 <h2 id="conclusion">Conclusion<a class="anchor" aria-label="anchor" href="#conclusion"></a>
@@ -629,7 +646,7 @@ Python.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/assets/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/assets/logo_umcg.svg" style="max-width: 150px;"></a></p>
+  <p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://amr-for-r.org/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://amr-for-r.org/logo_umcg.svg" style="max-width: 150px;"></a></p>
 </div>
 
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+<li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
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+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
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+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
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+</nav><div class="container template-article">
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+
+
+
+<div class="row">
+  <main id="main" class="col-md-9"><div class="page-header">
+      <img src="../logo.svg" class="logo" alt=""><h1>AMR with tidymodels</h1>
+            
+      
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/AMR_with_tidymodels.Rmd" class="external-link"><code>vignettes/AMR_with_tidymodels.Rmd</code></a></small>
+      <div class="d-none name"><code>AMR_with_tidymodels.Rmd</code></div>
+    </div>
+
+    
+    
+<blockquote>
+<p>This page was entirely written by our <a href="https://chat.amr-for-r.org" class="external-link">AMR for R Assistant</a>, a ChatGPT
+manually-trained model able to answer any question about the
+<code>AMR</code> package.</p>
+</blockquote>
+<p>Antimicrobial resistance (AMR) is a global health crisis, and
+understanding resistance patterns is crucial for managing effective
+treatments. The <code>AMR</code> R package provides robust tools for
+analysing AMR data, including convenient antimicrobial selector
+functions like <code><a href="../reference/antimicrobial_selectors.html">aminoglycosides()</a></code> and
+<code><a href="../reference/antimicrobial_selectors.html">betalactams()</a></code>.</p>
+<p>In this post, we will explore how to use the <code>tidymodels</code>
+framework to predict resistance patterns in the
+<code>example_isolates</code> dataset in two examples.</p>
+<p>This post contains the following examples:</p>
+<ol style="list-style-type: decimal">
+<li>Using Antimicrobial Selectors</li>
+<li>Predicting ESBL Presence Using Raw MICs</li>
+<li>Predicting AMR Over Time</li>
+</ol>
+<div class="section level2">
+<h2 id="example-1-using-antimicrobial-selectors">Example 1: Using Antimicrobial Selectors<a class="anchor" aria-label="anchor" href="#example-1-using-antimicrobial-selectors"></a>
+</h2>
+<p>By leveraging the power of <code>tidymodels</code> and the
+<code>AMR</code> package, we’ll build a reproducible machine learning
+workflow to predict the Gramstain of the microorganism to two important
+antibiotic classes: aminoglycosides and beta-lactams.</p>
+<div class="section level3">
+<h3 id="objective">
+<strong>Objective</strong><a class="anchor" aria-label="anchor" href="#objective"></a>
+</h3>
+<p>Our goal is to build a predictive model using the
+<code>tidymodels</code> framework to determine the Gramstain of the
+microorganism based on microbial data. We will:</p>
+<ol style="list-style-type: decimal">
+<li>Preprocess data using the selector functions
+<code><a href="../reference/antimicrobial_selectors.html">aminoglycosides()</a></code> and <code><a href="../reference/antimicrobial_selectors.html">betalactams()</a></code>.</li>
+<li>Define a logistic regression model for prediction.</li>
+<li>Use a structured <code>tidymodels</code> workflow to preprocess,
+train, and evaluate the model.</li>
+</ol>
+</div>
+<div class="section level3">
+<h3 id="data-preparation">
+<strong>Data Preparation</strong><a class="anchor" aria-label="anchor" href="#data-preparation"></a>
+</h3>
+<p>We begin by loading the required libraries and preparing the
+<code>example_isolates</code> dataset from the <code>AMR</code>
+package.</p>
+<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># Load required libraries</span></span>
+<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://amr-for-r.org">AMR</a></span><span class="op">)</span>          <span class="co"># For AMR data analysis</span></span>
+<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://tidymodels.tidymodels.org" class="external-link">tidymodels</a></span><span class="op">)</span>   <span class="co"># For machine learning workflows, and data manipulation (dplyr, tidyr, ...)</span></span></code></pre></div>
+<p>Prepare the data:</p>
+<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># Your data could look like this:</span></span>
+<span><span class="va">example_isolates</span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 2,000 × 46</span></span></span>
+<span><span class="co">#&gt;    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX  </span></span>
+<span><span class="co">#&gt;    <span style="color: #949494; font-style: italic;">&lt;date&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span></span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 1</span> 2002-01-02 A77334     65 F      Clinical <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #B2B2B2;">  NA</span>  <span style="color: #B2B2B2;">  NA</span> </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 2</span> 2002-01-03 A77334     65 F      Clinical <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #B2B2B2;">  NA</span>  <span style="color: #B2B2B2;">  NA</span> </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 3</span> 2002-01-07 067927     45 F      ICU      <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>EPDR <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span> </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 4</span> 2002-01-07 067927     45 F      ICU      <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>EPDR <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span> </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 5</span> 2002-01-13 067927     45 F      ICU      <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>EPDR <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span> </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 6</span> 2002-01-13 067927     45 F      ICU      <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>EPDR <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span> </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 7</span> 2002-01-14 462729     78 M      Clinical <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>AURS <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #080808; background-color: #5FD7AF;">  S  </span> <span style="color: #080808; background-color: #FFAFAF;">  R  </span></span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> 2002-01-14 462729     78 M      Clinical <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>AURS <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #080808; background-color: #5FD7AF;">  S  </span> <span style="color: #080808; background-color: #FFAFAF;">  R  </span></span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> 2002-01-16 067927     45 F      ICU      <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>EPDR <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span> </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> 2002-01-17 858515     79 F      ICU      <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>EPDR <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #080808; background-color: #5FD7AF;">  S  </span> <span style="color: #B2B2B2;">  NA</span> </span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 1,990 more rows</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 36 more variables: AMC &lt;sir&gt;, AMP &lt;sir&gt;, TZP &lt;sir&gt;, CZO &lt;sir&gt;, FEP &lt;sir&gt;,</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;">#   CXM &lt;sir&gt;, FOX &lt;sir&gt;, CTX &lt;sir&gt;, CAZ &lt;sir&gt;, CRO &lt;sir&gt;, GEN &lt;sir&gt;,</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;">#   TOB &lt;sir&gt;, AMK &lt;sir&gt;, KAN &lt;sir&gt;, TMP &lt;sir&gt;, SXT &lt;sir&gt;, NIT &lt;sir&gt;,</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;">#   FOS &lt;sir&gt;, LNZ &lt;sir&gt;, CIP &lt;sir&gt;, MFX &lt;sir&gt;, VAN &lt;sir&gt;, TEC &lt;sir&gt;,</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;">#   TCY &lt;sir&gt;, TGC &lt;sir&gt;, DOX &lt;sir&gt;, ERY &lt;sir&gt;, CLI &lt;sir&gt;, AZM &lt;sir&gt;,</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;">#   IPM &lt;sir&gt;, MEM &lt;sir&gt;, MTR &lt;sir&gt;, CHL &lt;sir&gt;, COL &lt;sir&gt;, MUP &lt;sir&gt;, …</span></span></span>
+<span></span>
+<span><span class="co"># Select relevant columns for prediction</span></span>
+<span><span class="va">data</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="co"># select AB results dynamically</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">mo</span>, <span class="fu"><a href="../reference/antimicrobial_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="../reference/antimicrobial_selectors.html">betalactams</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="co"># replace NAs with NI (not-interpretable)</span></span>
+<span>   <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu"><a href="https://tidyselect.r-lib.org/reference/where.html" class="external-link">where</a></span><span class="op">(</span><span class="va">is.sir</span><span class="op">)</span>,</span>
+<span>                 <span class="op">~</span><span class="fu">replace_na</span><span class="op">(</span><span class="va">.x</span>, <span class="st">"NI"</span><span class="op">)</span><span class="op">)</span>,</span>
+<span>          <span class="co"># make factors of SIR columns</span></span>
+<span>          <span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu"><a href="https://tidyselect.r-lib.org/reference/where.html" class="external-link">where</a></span><span class="op">(</span><span class="va">is.sir</span><span class="op">)</span>,</span>
+<span>                 <span class="va">as.integer</span><span class="op">)</span>,</span>
+<span>          <span class="co"># get Gramstain of microorganisms</span></span>
+<span>          mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/factor.html" class="external-link">as.factor</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="co"># drop NAs - the ones without a Gramstain (fungi, etc.)</span></span>
+<span>  <span class="fu">drop_na</span><span class="op">(</span><span class="op">)</span></span>
+<span><span class="co">#&gt; <span style="color: #0000BB;">ℹ For </span><span style="color: #0000BB; background-color: #EEEEEE;">`aminoglycosides()`</span><span style="color: #0000BB;"> using columns '</span><span style="color: #0000BB; font-weight: bold;">GEN</span><span style="color: #0000BB;">' (gentamicin), '</span><span style="color: #0000BB; font-weight: bold;">TOB</span><span style="color: #0000BB;">'</span></span></span>
+<span><span class="co"><span style="color: #0000BB;">#&gt;   (tobramycin), '</span><span style="color: #0000BB; font-weight: bold;">AMK</span><span style="color: #0000BB;">' (amikacin), and '</span><span style="color: #0000BB; font-weight: bold;">KAN</span><span style="color: #0000BB;">' (kanamycin)</span></span></span>
+<span><span class="co">#&gt; <span style="color: #0000BB;">ℹ For </span><span style="color: #0000BB; background-color: #EEEEEE;">`betalactams()`</span><span style="color: #0000BB;"> using columns '</span><span style="color: #0000BB; font-weight: bold;">PEN</span><span style="color: #0000BB;">' (benzylpenicillin), '</span><span style="color: #0000BB; font-weight: bold;">OXA</span><span style="color: #0000BB;">'</span></span></span>
+<span><span class="co"><span style="color: #0000BB;">#&gt;   (oxacillin), '</span><span style="color: #0000BB; font-weight: bold;">FLC</span><span style="color: #0000BB;">' (flucloxacillin), '</span><span style="color: #0000BB; font-weight: bold;">AMX</span><span style="color: #0000BB;">' (amoxicillin), '</span><span style="color: #0000BB; font-weight: bold;">AMC</span><span style="color: #0000BB;">'</span></span></span>
+<span><span class="co"><span style="color: #0000BB;">#&gt;   (amoxicillin/clavulanic acid), '</span><span style="color: #0000BB; font-weight: bold;">AMP</span><span style="color: #0000BB;">' (ampicillin), '</span><span style="color: #0000BB; font-weight: bold;">TZP</span><span style="color: #0000BB;">'</span></span></span>
+<span><span class="co"><span style="color: #0000BB;">#&gt;   (piperacillin/tazobactam), '</span><span style="color: #0000BB; font-weight: bold;">CZO</span><span style="color: #0000BB;">' (cefazolin), '</span><span style="color: #0000BB; font-weight: bold;">FEP</span><span style="color: #0000BB;">' (cefepime), '</span><span style="color: #0000BB; font-weight: bold;">CXM</span><span style="color: #0000BB;">'</span></span></span>
+<span><span class="co"><span style="color: #0000BB;">#&gt;   (cefuroxime), '</span><span style="color: #0000BB; font-weight: bold;">FOX</span><span style="color: #0000BB;">' (cefoxitin), '</span><span style="color: #0000BB; font-weight: bold;">CTX</span><span style="color: #0000BB;">' (cefotaxime), '</span><span style="color: #0000BB; font-weight: bold;">CAZ</span><span style="color: #0000BB;">' (ceftazidime),</span></span></span>
+<span><span class="co"><span style="color: #0000BB;">#&gt;   '</span><span style="color: #0000BB; font-weight: bold;">CRO</span><span style="color: #0000BB;">' (ceftriaxone), '</span><span style="color: #0000BB; font-weight: bold;">IPM</span><span style="color: #0000BB;">' (imipenem), and '</span><span style="color: #0000BB; font-weight: bold;">MEM</span><span style="color: #0000BB;">' (meropenem)</span></span></span></code></pre></div>
+<p><strong>Explanation:</strong></p>
+<ul>
+<li>
+<code><a href="../reference/antimicrobial_selectors.html">aminoglycosides()</a></code> and <code><a href="../reference/antimicrobial_selectors.html">betalactams()</a></code>
+dynamically select columns for antimicrobials in these classes.</li>
+<li>
+<code>drop_na()</code> ensures the model receives complete cases for
+training.</li>
+</ul>
+</div>
+<div class="section level3">
+<h3 id="defining-the-workflow">
+<strong>Defining the Workflow</strong><a class="anchor" aria-label="anchor" href="#defining-the-workflow"></a>
+</h3>
+<p>We now define the <code>tidymodels</code> workflow, which consists of
+three steps: preprocessing, model specification, and fitting.</p>
+<div class="section level4">
+<h4 id="preprocessing-with-a-recipe">1. Preprocessing with a Recipe<a class="anchor" aria-label="anchor" href="#preprocessing-with-a-recipe"></a>
+</h4>
+<p>We create a recipe to preprocess the data for modelling.</p>
+<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># Define the recipe for data preprocessing</span></span>
+<span><span class="va">resistance_recipe</span> <span class="op">&lt;-</span> <span class="fu">recipe</span><span class="op">(</span><span class="va">mo</span> <span class="op">~</span> <span class="va">.</span>, data <span class="op">=</span> <span class="va">data</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu">step_corr</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="../reference/antimicrobial_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="../reference/antimicrobial_selectors.html">betalactams</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>, threshold <span class="op">=</span> <span class="fl">0.9</span><span class="op">)</span></span>
+<span><span class="va">resistance_recipe</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; <span style="color: #00BBBB;">──</span> <span style="font-weight: bold;">Recipe</span> <span style="color: #00BBBB;">──────────────────────────────────────────────────────────────────────</span></span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; ── Inputs</span></span>
+<span><span class="co">#&gt; Number of variables by role</span></span>
+<span><span class="co">#&gt; outcome:    1</span></span>
+<span><span class="co">#&gt; predictor: 20</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; ── Operations</span></span>
+<span><span class="co">#&gt; <span style="color: #00BBBB;">•</span> Correlation filter on: <span style="color: #0000BB;">c(aminoglycosides(), betalactams())</span></span></span></code></pre></div>
+<p>For a recipe that includes at least one preprocessing operation, like
+we have with <code>step_corr()</code>, the necessary parameters can be
+estimated from a training set using <code>prep()</code>:</p>
+<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="fu">prep</span><span class="op">(</span><span class="va">resistance_recipe</span><span class="op">)</span></span>
+<span><span class="co">#&gt; <span style="color: #0000BB;">ℹ For </span><span style="color: #0000BB; background-color: #EEEEEE;">`aminoglycosides()`</span><span style="color: #0000BB;"> using columns '</span><span style="color: #0000BB; font-weight: bold;">GEN</span><span style="color: #0000BB;">' (gentamicin), '</span><span style="color: #0000BB; font-weight: bold;">TOB</span><span style="color: #0000BB;">'</span></span></span>
+<span><span class="co"><span style="color: #0000BB;">#&gt;   (tobramycin), '</span><span style="color: #0000BB; font-weight: bold;">AMK</span><span style="color: #0000BB;">' (amikacin), and '</span><span style="color: #0000BB; font-weight: bold;">KAN</span><span style="color: #0000BB;">' (kanamycin)</span></span></span>
+<span><span class="co">#&gt; <span style="color: #0000BB;">ℹ For </span><span style="color: #0000BB; background-color: #EEEEEE;">`betalactams()`</span><span style="color: #0000BB;"> using columns '</span><span style="color: #0000BB; font-weight: bold;">PEN</span><span style="color: #0000BB;">' (benzylpenicillin), '</span><span style="color: #0000BB; font-weight: bold;">OXA</span><span style="color: #0000BB;">'</span></span></span>
+<span><span class="co"><span style="color: #0000BB;">#&gt;   (oxacillin), '</span><span style="color: #0000BB; font-weight: bold;">FLC</span><span style="color: #0000BB;">' (flucloxacillin), '</span><span style="color: #0000BB; font-weight: bold;">AMX</span><span style="color: #0000BB;">' (amoxicillin), '</span><span style="color: #0000BB; font-weight: bold;">AMC</span><span style="color: #0000BB;">'</span></span></span>
+<span><span class="co"><span style="color: #0000BB;">#&gt;   (amoxicillin/clavulanic acid), '</span><span style="color: #0000BB; font-weight: bold;">AMP</span><span style="color: #0000BB;">' (ampicillin), '</span><span style="color: #0000BB; font-weight: bold;">TZP</span><span style="color: #0000BB;">'</span></span></span>
+<span><span class="co"><span style="color: #0000BB;">#&gt;   (piperacillin/tazobactam), '</span><span style="color: #0000BB; font-weight: bold;">CZO</span><span style="color: #0000BB;">' (cefazolin), '</span><span style="color: #0000BB; font-weight: bold;">FEP</span><span style="color: #0000BB;">' (cefepime), '</span><span style="color: #0000BB; font-weight: bold;">CXM</span><span style="color: #0000BB;">'</span></span></span>
+<span><span class="co"><span style="color: #0000BB;">#&gt;   (cefuroxime), '</span><span style="color: #0000BB; font-weight: bold;">FOX</span><span style="color: #0000BB;">' (cefoxitin), '</span><span style="color: #0000BB; font-weight: bold;">CTX</span><span style="color: #0000BB;">' (cefotaxime), '</span><span style="color: #0000BB; font-weight: bold;">CAZ</span><span style="color: #0000BB;">' (ceftazidime),</span></span></span>
+<span><span class="co"><span style="color: #0000BB;">#&gt;   '</span><span style="color: #0000BB; font-weight: bold;">CRO</span><span style="color: #0000BB;">' (ceftriaxone), '</span><span style="color: #0000BB; font-weight: bold;">IPM</span><span style="color: #0000BB;">' (imipenem), and '</span><span style="color: #0000BB; font-weight: bold;">MEM</span><span style="color: #0000BB;">' (meropenem)</span></span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; <span style="color: #00BBBB;">──</span> <span style="font-weight: bold;">Recipe</span> <span style="color: #00BBBB;">──────────────────────────────────────────────────────────────────────</span></span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; ── Inputs</span></span>
+<span><span class="co">#&gt; Number of variables by role</span></span>
+<span><span class="co">#&gt; outcome:    1</span></span>
+<span><span class="co">#&gt; predictor: 20</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; ── Training information</span></span>
+<span><span class="co">#&gt; Training data contained 1968 data points and no incomplete rows.</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; ── Operations</span></span>
+<span><span class="co">#&gt; <span style="color: #00BBBB;">•</span> Correlation filter on: <span style="color: #0000BB;">AMX</span> <span style="color: #0000BB;">CTX</span> | <span style="font-style: italic;">Trained</span></span></span></code></pre></div>
+<p><strong>Explanation:</strong></p>
+<ul>
+<li>
+<code>recipe(mo ~ ., data = data)</code> will take the
+<code>mo</code> column as outcome and all other columns as
+predictors.</li>
+<li>
+<code>step_corr()</code> removes predictors (i.e., antibiotic
+columns) that have a higher correlation than 90%.</li>
+</ul>
+<p>Notice how the recipe contains just the antimicrobial selector
+functions - no need to define the columns specifically. In the
+preparation (retrieved with <code>prep()</code>) we can see that the
+columns or variables ‘AMX’ and ‘CTX’ were removed as they correlate too
+much with existing, other variables.</p>
+</div>
+<div class="section level4">
+<h4 id="specifying-the-model">2. Specifying the Model<a class="anchor" aria-label="anchor" href="#specifying-the-model"></a>
+</h4>
+<p>We define a logistic regression model since resistance prediction is
+a binary classification task.</p>
+<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># Specify a logistic regression model</span></span>
+<span><span class="va">logistic_model</span> <span class="op">&lt;-</span> <span class="fu">logistic_reg</span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu">set_engine</span><span class="op">(</span><span class="st">"glm"</span><span class="op">)</span> <span class="co"># Use the Generalised Linear Model engine</span></span>
+<span><span class="va">logistic_model</span></span>
+<span><span class="co">#&gt; Logistic Regression Model Specification (classification)</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; Computational engine: glm</span></span></code></pre></div>
+<p><strong>Explanation:</strong></p>
+<ul>
+<li>
+<code>logistic_reg()</code> sets up a logistic regression
+model.</li>
+<li>
+<code>set_engine("glm")</code> specifies the use of R’s built-in GLM
+engine.</li>
+</ul>
+</div>
+<div class="section level4">
+<h4 id="building-the-workflow">3. Building the Workflow<a class="anchor" aria-label="anchor" href="#building-the-workflow"></a>
+</h4>
+<p>We bundle the recipe and model together into a <code>workflow</code>,
+which organises the entire modelling process.</p>
+<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># Combine the recipe and model into a workflow</span></span>
+<span><span class="va">resistance_workflow</span> <span class="op">&lt;-</span> <span class="fu">workflow</span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu">add_recipe</span><span class="op">(</span><span class="va">resistance_recipe</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="co"># Add the preprocessing recipe</span></span>
+<span>  <span class="fu">add_model</span><span class="op">(</span><span class="va">logistic_model</span><span class="op">)</span> <span class="co"># Add the logistic regression model</span></span>
+<span><span class="va">resistance_workflow</span></span>
+<span><span class="co">#&gt; ══ Workflow ════════════════════════════════════════════════════════════════════</span></span>
+<span><span class="co">#&gt; <span style="font-style: italic;">Preprocessor:</span> Recipe</span></span>
+<span><span class="co">#&gt; <span style="font-style: italic;">Model:</span> logistic_reg()</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; ── Preprocessor ────────────────────────────────────────────────────────────────</span></span>
+<span><span class="co">#&gt; 1 Recipe Step</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; • step_corr()</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; ── Model ───────────────────────────────────────────────────────────────────────</span></span>
+<span><span class="co">#&gt; Logistic Regression Model Specification (classification)</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; Computational engine: glm</span></span></code></pre></div>
+</div>
+</div>
+<div class="section level3">
+<h3 id="training-and-evaluating-the-model">
+<strong>Training and Evaluating the Model</strong><a class="anchor" aria-label="anchor" href="#training-and-evaluating-the-model"></a>
+</h3>
+<p>To train the model, we split the data into training and testing sets.
+Then, we fit the workflow on the training set and evaluate its
+performance.</p>
+<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># Split data into training and testing sets</span></span>
+<span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">123</span><span class="op">)</span> <span class="co"># For reproducibility</span></span>
+<span><span class="va">data_split</span> <span class="op">&lt;-</span> <span class="fu">initial_split</span><span class="op">(</span><span class="va">data</span>, prop <span class="op">=</span> <span class="fl">0.8</span><span class="op">)</span> <span class="co"># 80% training, 20% testing</span></span>
+<span><span class="va">training_data</span> <span class="op">&lt;-</span> <span class="fu">training</span><span class="op">(</span><span class="va">data_split</span><span class="op">)</span> <span class="co"># Training set</span></span>
+<span><span class="va">testing_data</span> <span class="op">&lt;-</span> <span class="fu">testing</span><span class="op">(</span><span class="va">data_split</span><span class="op">)</span>   <span class="co"># Testing set</span></span>
+<span></span>
+<span><span class="co"># Fit the workflow to the training data</span></span>
+<span><span class="va">fitted_workflow</span> <span class="op">&lt;-</span> <span class="va">resistance_workflow</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu">fit</span><span class="op">(</span><span class="va">training_data</span><span class="op">)</span> <span class="co"># Train the model</span></span></code></pre></div>
+<p><strong>Explanation:</strong></p>
+<ul>
+<li>
+<code>initial_split()</code> splits the data into training and
+testing sets.</li>
+<li>
+<code>fit()</code> trains the workflow on the training set.</li>
+</ul>
+<p>Notice how in <code>fit()</code>, the antimicrobial selector
+functions are internally called again. For training, these functions are
+called since they are stored in the recipe.</p>
+<p>Next, we evaluate the model on the testing data.</p>
+<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># Make predictions on the testing set</span></span>
+<span><span class="va">predictions</span> <span class="op">&lt;-</span> <span class="va">fitted_workflow</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu"><a href="https://rdrr.io/r/stats/predict.html" class="external-link">predict</a></span><span class="op">(</span><span class="va">testing_data</span><span class="op">)</span>                <span class="co"># Generate predictions</span></span>
+<span><span class="va">probabilities</span> <span class="op">&lt;-</span> <span class="va">fitted_workflow</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu"><a href="https://rdrr.io/r/stats/predict.html" class="external-link">predict</a></span><span class="op">(</span><span class="va">testing_data</span>, type <span class="op">=</span> <span class="st">"prob"</span><span class="op">)</span> <span class="co"># Generate probabilities</span></span>
+<span></span>
+<span><span class="va">predictions</span> <span class="op">&lt;-</span> <span class="va">predictions</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/bind_cols.html" class="external-link">bind_cols</a></span><span class="op">(</span><span class="va">probabilities</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/bind_cols.html" class="external-link">bind_cols</a></span><span class="op">(</span><span class="va">testing_data</span><span class="op">)</span> <span class="co"># Combine with true labels</span></span>
+<span></span>
+<span><span class="va">predictions</span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 394 × 24</span></span></span>
+<span><span class="co">#&gt;    .pred_class   `.pred_Gram-negative` `.pred_Gram-positive` mo        GEN   TOB</span></span>
+<span><span class="co">#&gt;    <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>                         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>                 <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 1</span> Gram-positive              1.07<span style="color: #949494;">e</span><span style="color: #BB0000;">- 1</span>             8.93 <span style="color: #949494;">e</span><span style="color: #BB0000;">- 1</span> Gram-p…     5     5</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 2</span> Gram-positive              3.17<span style="color: #949494;">e</span><span style="color: #BB0000;">- 8</span>             1.000<span style="color: #949494;">e</span>+ 0 Gram-p…     5     1</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 3</span> Gram-negative              9.99<span style="color: #949494;">e</span><span style="color: #BB0000;">- 1</span>             1.42 <span style="color: #949494;">e</span><span style="color: #BB0000;">- 3</span> Gram-n…     5     5</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 4</span> Gram-positive              2.22<span style="color: #949494;">e</span><span style="color: #BB0000;">-16</span>             1    <span style="color: #949494;">e</span>+ 0 Gram-p…     5     5</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 5</span> Gram-negative              9.46<span style="color: #949494;">e</span><span style="color: #BB0000;">- 1</span>             5.42 <span style="color: #949494;">e</span><span style="color: #BB0000;">- 2</span> Gram-n…     5     5</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 6</span> Gram-positive              1.07<span style="color: #949494;">e</span><span style="color: #BB0000;">- 1</span>             8.93 <span style="color: #949494;">e</span><span style="color: #BB0000;">- 1</span> Gram-p…     5     5</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 7</span> Gram-positive              2.22<span style="color: #949494;">e</span><span style="color: #BB0000;">-16</span>             1    <span style="color: #949494;">e</span>+ 0 Gram-p…     1     5</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> Gram-positive              2.22<span style="color: #949494;">e</span><span style="color: #BB0000;">-16</span>             1    <span style="color: #949494;">e</span>+ 0 Gram-p…     4     4</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> Gram-negative              1   <span style="color: #949494;">e</span>+ 0             2.22 <span style="color: #949494;">e</span><span style="color: #BB0000;">-16</span> Gram-n…     1     1</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> Gram-positive              6.05<span style="color: #949494;">e</span><span style="color: #BB0000;">-11</span>             1.000<span style="color: #949494;">e</span>+ 0 Gram-p…     4     4</span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 384 more rows</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 18 more variables: AMK &lt;int&gt;, KAN &lt;int&gt;, PEN &lt;int&gt;, OXA &lt;int&gt;, FLC &lt;int&gt;,</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;">#   AMX &lt;int&gt;, AMC &lt;int&gt;, AMP &lt;int&gt;, TZP &lt;int&gt;, CZO &lt;int&gt;, FEP &lt;int&gt;,</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;">#   CXM &lt;int&gt;, FOX &lt;int&gt;, CTX &lt;int&gt;, CAZ &lt;int&gt;, CRO &lt;int&gt;, IPM &lt;int&gt;, MEM &lt;int&gt;</span></span></span>
+<span></span>
+<span><span class="co"># Evaluate model performance</span></span>
+<span><span class="va">metrics</span> <span class="op">&lt;-</span> <span class="va">predictions</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu">metrics</span><span class="op">(</span>truth <span class="op">=</span> <span class="va">mo</span>, estimate <span class="op">=</span> <span class="va">.pred_class</span><span class="op">)</span> <span class="co"># Calculate performance metrics</span></span>
+<span></span>
+<span><span class="va">metrics</span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 2 × 3</span></span></span>
+<span><span class="co">#&gt;   .metric  .estimator .estimate</span></span>
+<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>          <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> accuracy binary         0.995</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> kap      binary         0.989</span></span>
+<span></span>
+<span></span>
+<span><span class="co"># To assess some other model properties, you can make our own `metrics()` function</span></span>
+<span><span class="va">our_metrics</span> <span class="op">&lt;-</span> <span class="fu">metric_set</span><span class="op">(</span><span class="va">accuracy</span>, <span class="va">kap</span>, <span class="va">ppv</span>, <span class="va">npv</span><span class="op">)</span> <span class="co"># add Positive Predictive Value and Negative Predictive Value</span></span>
+<span><span class="va">metrics2</span> <span class="op">&lt;-</span> <span class="va">predictions</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu">our_metrics</span><span class="op">(</span>truth <span class="op">=</span> <span class="va">mo</span>, estimate <span class="op">=</span> <span class="va">.pred_class</span><span class="op">)</span> <span class="co"># run again on our `our_metrics()` function</span></span>
+<span></span>
+<span><span class="va">metrics2</span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 4 × 3</span></span></span>
+<span><span class="co">#&gt;   .metric  .estimator .estimate</span></span>
+<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>          <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> accuracy binary         0.995</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> kap      binary         0.989</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> ppv      binary         0.987</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> npv      binary         1</span></span></code></pre></div>
+<p><strong>Explanation:</strong></p>
+<ul>
+<li>
+<code><a href="https://rdrr.io/r/stats/predict.html" class="external-link">predict()</a></code> generates predictions on the testing
+set.</li>
+<li>
+<code>metrics()</code> computes evaluation metrics like accuracy and
+kappa.</li>
+</ul>
+<p>It appears we can predict the Gram stain with a 99.5% accuracy based
+on AMR results of only aminoglycosides and beta-lactam antibiotics. The
+ROC curve looks like this:</p>
+<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">predictions</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu">roc_curve</span><span class="op">(</span><span class="va">mo</span>, <span class="va">`.pred_Gram-negative`</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
+<p><img src="AMR_with_tidymodels_files/figure-html/unnamed-chunk-8-1.png" width="720"></p>
+</div>
+<div class="section level3">
+<h3 id="conclusion">
+<strong>Conclusion</strong><a class="anchor" aria-label="anchor" href="#conclusion"></a>
+</h3>
+<p>In this post, we demonstrated how to build a machine learning
+pipeline with the <code>tidymodels</code> framework and the
+<code>AMR</code> package. By combining selector functions like
+<code><a href="../reference/antimicrobial_selectors.html">aminoglycosides()</a></code> and <code><a href="../reference/antimicrobial_selectors.html">betalactams()</a></code> with
+<code>tidymodels</code>, we efficiently prepared data, trained a model,
+and evaluated its performance.</p>
+<p>This workflow is extensible to other antimicrobial classes and
+resistance patterns, empowering users to analyse AMR data systematically
+and reproducibly.</p>
+<hr>
+</div>
+</div>
+<div class="section level2">
+<h2 id="example-2-predicting-esbl-presence-using-raw-mics">Example 2: Predicting ESBL Presence Using Raw MICs<a class="anchor" aria-label="anchor" href="#example-2-predicting-esbl-presence-using-raw-mics"></a>
+</h2>
+<p>In this second example, we demonstrate how to use
+<code>&lt;mic&gt;</code> columns directly in <code>tidymodels</code>
+workflows using AMR-specific recipe steps. This includes a
+transformation to <code>log2</code> scale using
+<code>step_mic_log2()</code>, which prepares MIC values for use in
+classification models.</p>
+<p>This approach and idea formed the basis for the publication <a href="https://doi.org/10.3389/fmicb.2025.1582703" class="external-link">DOI:
+10.3389/fmicb.2025.1582703</a> to model the presence of
+extended-spectrum beta-lactamases (ESBL).</p>
+<blockquote>
+<p>NOTE: THIS EXAMPLE WILL BE AVAILABLE IN A NEXT VERSION (#TODO)</p>
+<p>The new AMR package version will contain new tidymodels selectors
+such as <code>step_mic_log2()</code>.</p>
+</blockquote>
+<!-- TODO for AMR v3.1.0: add info from here: https://github.com/msberends/AMR/blob/2461631bcefa78ebdb37bdfad359be74cdd9165a/vignettes/AMR_with_tidymodels.Rmd#L212-L291 -->
+<hr>
+</div>
+<div class="section level2">
+<h2 id="example-2-predicting-amr-over-time">Example 2: Predicting AMR Over Time<a class="anchor" aria-label="anchor" href="#example-2-predicting-amr-over-time"></a>
+</h2>
+<p>In this third example, we aim to predict antimicrobial resistance
+(AMR) trends over time using <code>tidymodels</code>. We will model
+resistance to three antibiotics (amoxicillin <code>AMX</code>,
+amoxicillin-clavulanic acid <code>AMC</code>, and ciprofloxacin
+<code>CIP</code>), based on historical data grouped by year and hospital
+ward.</p>
+<div class="section level3">
+<h3 id="objective-1">
+<strong>Objective</strong><a class="anchor" aria-label="anchor" href="#objective-1"></a>
+</h3>
+<p>Our goal is to:</p>
+<ol style="list-style-type: decimal">
+<li>Prepare the dataset by aggregating resistance data over time.</li>
+<li>Define a regression model to predict AMR trends.</li>
+<li>Use <code>tidymodels</code> to preprocess, train, and evaluate the
+model.</li>
+</ol>
+</div>
+<div class="section level3">
+<h3 id="data-preparation-1">
+<strong>Data Preparation</strong><a class="anchor" aria-label="anchor" href="#data-preparation-1"></a>
+</h3>
+<p>We start by transforming the <code>example_isolates</code> dataset
+into a structured time-series format.</p>
+<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># Load required libraries</span></span>
+<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://amr-for-r.org">AMR</a></span><span class="op">)</span></span>
+<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://tidymodels.tidymodels.org" class="external-link">tidymodels</a></span><span class="op">)</span></span>
+<span></span>
+<span><span class="co"># Transform dataset</span></span>
+<span><span class="va">data_time</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu"><a href="../reference/top_n_microorganisms.html">top_n_microorganisms</a></span><span class="op">(</span>n <span class="op">=</span> <span class="fl">10</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="co"># Filter on the top #10 species</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>year <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/integer.html" class="external-link">as.integer</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/format.html" class="external-link">format</a></span><span class="op">(</span><span class="va">date</span>, <span class="st">"%Y"</span><span class="op">)</span><span class="op">)</span>,  <span class="co"># Extract year from date</span></span>
+<span>         gramstain <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="co"># Get taxonomic names</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">year</span>, <span class="va">gramstain</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="va">AMX</span>, <span class="va">AMC</span>, <span class="va">CIP</span><span class="op">)</span>, </span>
+<span>                   <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="../reference/proportion.html">resistance</a></span><span class="op">(</span><span class="va">x</span>, minimum <span class="op">=</span> <span class="fl">0</span><span class="op">)</span>,</span>
+<span>                   .names <span class="op">=</span> <span class="st">"res_{.col}"</span><span class="op">)</span>, </span>
+<span>            .groups <span class="op">=</span> <span class="st">"drop"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> </span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="op">!</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">res_AMX</span><span class="op">)</span> <span class="op">&amp;</span> <span class="op">!</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">res_AMC</span><span class="op">)</span> <span class="op">&amp;</span> <span class="op">!</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">res_CIP</span><span class="op">)</span><span class="op">)</span> <span class="co"># Drop missing values</span></span>
+<span><span class="co">#&gt; <span style="color: #0000BB;">ℹ Using column '</span><span style="color: #0000BB; font-weight: bold;">mo</span><span style="color: #0000BB;">' as input for </span><span style="color: #0000BB; background-color: #EEEEEE;">`col_mo`</span><span style="color: #0000BB;">.</span></span></span>
+<span></span>
+<span><span class="va">data_time</span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 32 × 5</span></span></span>
+<span><span class="co">#&gt;     year gramstain     res_AMX res_AMC res_CIP</span></span>
+<span><span class="co">#&gt;    <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>           <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 1</span>  <span style="text-decoration: underline;">2</span>002 Gram-negative   1      0.105   0.060<span style="text-decoration: underline;">6</span></span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 2</span>  <span style="text-decoration: underline;">2</span>002 Gram-positive   0.838  0.182   0.162 </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 3</span>  <span style="text-decoration: underline;">2</span>003 Gram-negative   1      0.071<span style="text-decoration: underline;">4</span>  0     </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 4</span>  <span style="text-decoration: underline;">2</span>003 Gram-positive   0.714  0.244   0.154 </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 5</span>  <span style="text-decoration: underline;">2</span>004 Gram-negative   0.464  0.093<span style="text-decoration: underline;">8</span>  0     </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 6</span>  <span style="text-decoration: underline;">2</span>004 Gram-positive   0.849  0.299   0.244 </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 7</span>  <span style="text-decoration: underline;">2</span>005 Gram-negative   0.412  0.132   0.058<span style="text-decoration: underline;">8</span></span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span>  <span style="text-decoration: underline;">2</span>005 Gram-positive   0.882  0.382   0.154 </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span>  <span style="text-decoration: underline;">2</span>006 Gram-negative   0.379  0       0.1   </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span>  <span style="text-decoration: underline;">2</span>006 Gram-positive   0.778  0.333   0.353 </span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 22 more rows</span></span></span></code></pre></div>
+<p><strong>Explanation:</strong></p>
+<ul>
+<li>
+<code>mo_name(mo)</code>: Converts microbial codes into proper
+species names.</li>
+<li>
+<code><a href="../reference/proportion.html">resistance()</a></code>: Converts AMR results into numeric values
+(proportion of resistant isolates).</li>
+<li>
+<code>group_by(year, ward, species)</code>: Aggregates resistance
+rates by year and ward.</li>
+</ul>
+</div>
+<div class="section level3">
+<h3 id="defining-the-workflow-1">
+<strong>Defining the Workflow</strong><a class="anchor" aria-label="anchor" href="#defining-the-workflow-1"></a>
+</h3>
+<p>We now define the modelling workflow, which consists of a
+preprocessing step, a model specification, and the fitting process.</p>
+<div class="section level4">
+<h4 id="preprocessing-with-a-recipe-1">1. Preprocessing with a Recipe<a class="anchor" aria-label="anchor" href="#preprocessing-with-a-recipe-1"></a>
+</h4>
+<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># Define the recipe</span></span>
+<span><span class="va">resistance_recipe_time</span> <span class="op">&lt;-</span> <span class="fu">recipe</span><span class="op">(</span><span class="va">res_AMX</span> <span class="op">~</span> <span class="va">year</span> <span class="op">+</span> <span class="va">gramstain</span>, data <span class="op">=</span> <span class="va">data_time</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu">step_dummy</span><span class="op">(</span><span class="va">gramstain</span>, one_hot <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span>  <span class="co"># Convert categorical to numerical</span></span>
+<span>  <span class="fu">step_normalize</span><span class="op">(</span><span class="va">year</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span>  <span class="co"># Normalise year for better model performance</span></span>
+<span>  <span class="fu">step_nzv</span><span class="op">(</span><span class="fu">all_predictors</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>  <span class="co"># Remove near-zero variance predictors</span></span>
+<span></span>
+<span><span class="va">resistance_recipe_time</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; <span style="color: #00BBBB;">──</span> <span style="font-weight: bold;">Recipe</span> <span style="color: #00BBBB;">──────────────────────────────────────────────────────────────────────</span></span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; ── Inputs</span></span>
+<span><span class="co">#&gt; Number of variables by role</span></span>
+<span><span class="co">#&gt; outcome:   1</span></span>
+<span><span class="co">#&gt; predictor: 2</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; ── Operations</span></span>
+<span><span class="co">#&gt; <span style="color: #00BBBB;">•</span> Dummy variables from: <span style="color: #0000BB;">gramstain</span></span></span>
+<span><span class="co">#&gt; <span style="color: #00BBBB;">•</span> Centering and scaling for: <span style="color: #0000BB;">year</span></span></span>
+<span><span class="co">#&gt; <span style="color: #00BBBB;">•</span> Sparse, unbalanced variable filter on: <span style="color: #0000BB;">all_predictors()</span></span></span></code></pre></div>
+<p><strong>Explanation:</strong></p>
+<ul>
+<li>
+<code>step_dummy()</code>: Encodes categorical variables
+(<code>ward</code>, <code>species</code>) as numerical indicators.</li>
+<li>
+<code>step_normalize()</code>: Normalises the <code>year</code>
+variable.</li>
+<li>
+<code>step_nzv()</code>: Removes near-zero variance predictors.</li>
+</ul>
+</div>
+<div class="section level4">
+<h4 id="specifying-the-model-1">2. Specifying the Model<a class="anchor" aria-label="anchor" href="#specifying-the-model-1"></a>
+</h4>
+<p>We use a linear regression model to predict resistance trends.</p>
+<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># Define the linear regression model</span></span>
+<span><span class="va">lm_model</span> <span class="op">&lt;-</span> <span class="fu">linear_reg</span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu">set_engine</span><span class="op">(</span><span class="st">"lm"</span><span class="op">)</span> <span class="co"># Use linear regression</span></span>
+<span></span>
+<span><span class="va">lm_model</span></span>
+<span><span class="co">#&gt; Linear Regression Model Specification (regression)</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; Computational engine: lm</span></span></code></pre></div>
+<p><strong>Explanation:</strong></p>
+<ul>
+<li>
+<code>linear_reg()</code>: Defines a linear regression model.</li>
+<li>
+<code>set_engine("lm")</code>: Uses R’s built-in linear regression
+engine.</li>
+</ul>
+</div>
+<div class="section level4">
+<h4 id="building-the-workflow-1">3. Building the Workflow<a class="anchor" aria-label="anchor" href="#building-the-workflow-1"></a>
+</h4>
+<p>We combine the preprocessing recipe and model into a workflow.</p>
+<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># Create workflow</span></span>
+<span><span class="va">resistance_workflow_time</span> <span class="op">&lt;-</span> <span class="fu">workflow</span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu">add_recipe</span><span class="op">(</span><span class="va">resistance_recipe_time</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu">add_model</span><span class="op">(</span><span class="va">lm_model</span><span class="op">)</span></span>
+<span></span>
+<span><span class="va">resistance_workflow_time</span></span>
+<span><span class="co">#&gt; ══ Workflow ════════════════════════════════════════════════════════════════════</span></span>
+<span><span class="co">#&gt; <span style="font-style: italic;">Preprocessor:</span> Recipe</span></span>
+<span><span class="co">#&gt; <span style="font-style: italic;">Model:</span> linear_reg()</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; ── Preprocessor ────────────────────────────────────────────────────────────────</span></span>
+<span><span class="co">#&gt; 3 Recipe Steps</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; • step_dummy()</span></span>
+<span><span class="co">#&gt; • step_normalize()</span></span>
+<span><span class="co">#&gt; • step_nzv()</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; ── Model ───────────────────────────────────────────────────────────────────────</span></span>
+<span><span class="co">#&gt; Linear Regression Model Specification (regression)</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; Computational engine: lm</span></span></code></pre></div>
+</div>
+</div>
+<div class="section level3">
+<h3 id="training-and-evaluating-the-model-1">
+<strong>Training and Evaluating the Model</strong><a class="anchor" aria-label="anchor" href="#training-and-evaluating-the-model-1"></a>
+</h3>
+<p>We split the data into training and testing sets, fit the model, and
+evaluate performance.</p>
+<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># Split the data</span></span>
+<span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">123</span><span class="op">)</span></span>
+<span><span class="va">data_split_time</span> <span class="op">&lt;-</span> <span class="fu">initial_split</span><span class="op">(</span><span class="va">data_time</span>, prop <span class="op">=</span> <span class="fl">0.8</span><span class="op">)</span></span>
+<span><span class="va">train_time</span> <span class="op">&lt;-</span> <span class="fu">training</span><span class="op">(</span><span class="va">data_split_time</span><span class="op">)</span></span>
+<span><span class="va">test_time</span> <span class="op">&lt;-</span> <span class="fu">testing</span><span class="op">(</span><span class="va">data_split_time</span><span class="op">)</span></span>
+<span></span>
+<span><span class="co"># Train the model</span></span>
+<span><span class="va">fitted_workflow_time</span> <span class="op">&lt;-</span> <span class="va">resistance_workflow_time</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu">fit</span><span class="op">(</span><span class="va">train_time</span><span class="op">)</span></span>
+<span></span>
+<span><span class="co"># Make predictions</span></span>
+<span><span class="va">predictions_time</span> <span class="op">&lt;-</span> <span class="va">fitted_workflow_time</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu"><a href="https://rdrr.io/r/stats/predict.html" class="external-link">predict</a></span><span class="op">(</span><span class="va">test_time</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/bind_cols.html" class="external-link">bind_cols</a></span><span class="op">(</span><span class="va">test_time</span><span class="op">)</span> </span>
+<span></span>
+<span><span class="co"># Evaluate model</span></span>
+<span><span class="va">metrics_time</span> <span class="op">&lt;-</span> <span class="va">predictions_time</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu">metrics</span><span class="op">(</span>truth <span class="op">=</span> <span class="va">res_AMX</span>, estimate <span class="op">=</span> <span class="va">.pred</span><span class="op">)</span></span>
+<span></span>
+<span><span class="va">metrics_time</span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 3 × 3</span></span></span>
+<span><span class="co">#&gt;   .metric .estimator .estimate</span></span>
+<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>          <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> rmse    standard      0.077<span style="text-decoration: underline;">4</span></span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> rsq     standard      0.711 </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> mae     standard      0.070<span style="text-decoration: underline;">4</span></span></span></code></pre></div>
+<p><strong>Explanation:</strong></p>
+<ul>
+<li>
+<code>initial_split()</code>: Splits data into training and testing
+sets.</li>
+<li>
+<code>fit()</code>: Trains the workflow.</li>
+<li>
+<code><a href="https://rdrr.io/r/stats/predict.html" class="external-link">predict()</a></code>: Generates resistance predictions.</li>
+<li>
+<code>metrics()</code>: Evaluates model performance.</li>
+</ul>
+</div>
+<div class="section level3">
+<h3 id="visualising-predictions">
+<strong>Visualising Predictions</strong><a class="anchor" aria-label="anchor" href="#visualising-predictions"></a>
+</h3>
+<p>We plot resistance trends over time for amoxicillin.</p>
+<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span>
+<span></span>
+<span><span class="co"># Plot actual vs predicted resistance over time</span></span>
+<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">predictions_time</span>, <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">year</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>y <span class="op">=</span> <span class="va">res_AMX</span>, color <span class="op">=</span> <span class="st">"Actual"</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_path.html" class="external-link">geom_line</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>y <span class="op">=</span> <span class="va">.pred</span>, color <span class="op">=</span> <span class="st">"Predicted"</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>title <span class="op">=</span> <span class="st">"Predicted vs Actual AMX Resistance Over Time"</span>,</span>
+<span>       x <span class="op">=</span> <span class="st">"Year"</span>,</span>
+<span>       y <span class="op">=</span> <span class="st">"Resistance Proportion"</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_minimal</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
+<p><img src="AMR_with_tidymodels_files/figure-html/unnamed-chunk-14-1.png" width="720"></p>
+<p>Additionally, we can visualise resistance trends in
+<code>ggplot2</code> and directly add linear models there:</p>
+<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">data_time</span>, <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">year</span>, y <span class="op">=</span> <span class="va">res_AMX</span>, color <span class="op">=</span> <span class="va">gramstain</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_path.html" class="external-link">geom_line</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>title <span class="op">=</span> <span class="st">"AMX Resistance Trends"</span>,</span>
+<span>       x <span class="op">=</span> <span class="st">"Year"</span>,</span>
+<span>       y <span class="op">=</span> <span class="st">"Resistance Proportion"</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="co"># add a linear model directly in ggplot2:</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_smooth.html" class="external-link">geom_smooth</a></span><span class="op">(</span>method <span class="op">=</span> <span class="st">"lm"</span>,</span>
+<span>              formula <span class="op">=</span> <span class="va">y</span> <span class="op">~</span> <span class="va">x</span>,</span>
+<span>              alpha <span class="op">=</span> <span class="fl">0.25</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_minimal</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
+<p><img src="AMR_with_tidymodels_files/figure-html/unnamed-chunk-15-1.png" width="720"></p>
+</div>
+<div class="section level3">
+<h3 id="conclusion-1">
+<strong>Conclusion</strong><a class="anchor" aria-label="anchor" href="#conclusion-1"></a>
+</h3>
+<p>In this example, we demonstrated how to analyze AMR trends over time
+using <code>tidymodels</code>. By aggregating resistance rates by year
+and hospital ward, we built a predictive model to track changes in
+resistance to amoxicillin (<code>AMX</code>), amoxicillin-clavulanic
+acid (<code>AMC</code>), and ciprofloxacin (<code>CIP</code>).</p>
+<p>This method can be extended to other antibiotics and resistance
+patterns, providing valuable insights into AMR dynamics in healthcare
+settings.</p>
+</div>
+</div>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
+    </nav></aside>
+</div>
+
+
+
+    <footer><div class="pkgdown-footer-left">
+  <p><code>AMR</code> (for R). Free and open-source, licenced under the <a target="_blank" href="https://github.com/msberends/AMR/blob/main/LICENSE" class="external-link">GNU General Public License version 2.0 (GPL-2)</a>.<br>Developed at the <a target="_blank" href="https://www.rug.nl" class="external-link">University of Groningen</a> and <a target="_blank" href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a> in The Netherlands.</p>
+</div>
+
+<div class="pkgdown-footer-right">
+  <p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://amr-for-r.org/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://amr-for-r.org/logo_umcg.svg" style="max-width: 150px;"></a></p>
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articles/EUCAST.html

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-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9099</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9033</small>
 
 
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@@ -43,13 +44,13 @@
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+    <li><a class="dropdown-item" href="../articles/AMR_with_tidymodels.html"><span class="fa fa-square-root-variable"></span> Use AMR for Predictive Modelling (tidymodels)</a></li>
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-    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../reference/mdro.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
     <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
-    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply EUCAST Rules</a></li>
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@@ -74,7 +78,7 @@
 
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.svg" class="logo" alt=""><h1>How to apply EUCAST rules</h1>
+      <img src="../logo.svg" class="logo" alt=""><h1>Apply EUCAST rules</h1>
             
       
       <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/EUCAST.Rmd" class="external-link"><code>vignettes/EUCAST.Rmd</code></a></small>
@@ -87,78 +91,79 @@
 <h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
 </h2>
 <p>What are EUCAST rules? The European Committee on Antimicrobial
-Susceptibility Testing (EUCAST) states <a href="https://www.eucast.org/expert_rules_and_intrinsic_resistance/" class="external-link">on
+Susceptibility Testing (EUCAST) states <a href="https://www.eucast.org/expert_rules_and_expected_phenotypes" class="external-link">on
 their website</a>:</p>
 <blockquote>
-<p><em>EUCAST expert rules are a tabulated collection of expert
-knowledge on intrinsic resistances, exceptional resistance phenotypes
-and interpretive rules that may be applied to antimicrobial
-susceptibility testing in order to reduce errors and make appropriate
-recommendations for reporting particular resistances.</em></p>
+<p><em>EUCAST expert rules (see below) are a tabulated collection of
+expert knowledge on interpretive rules, expected resistant phenotypes
+and expected susceptible phenotypes which should be applied to
+antimicrobial susceptibility testing in order to reduce testing, reduce
+errors and make appropriate recommendations for reporting particular
+resistances.</em></p>
 </blockquote>
 <p>In Europe, a lot of medical microbiological laboratories already
 apply these rules (<a href="https://www.eurosurveillance.org/content/10.2807/1560-7917.ES2015.20.2.21008" class="external-link">Brown
 <em>et al.</em>, 2015</a>). Our package features their latest insights
-on intrinsic resistance and unusual phenotypes (v3.1, 2016).</p>
-<p>Moreover, the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function we use for this
-purpose can also apply additional rules, like forcing
-<help title="ATC: J01CA01">ampicillin</help> = R in isolates when
-<help title="ATC: J01CR02">amoxicillin/clavulanic acid</help> = R.</p>
+on expected resistant phenotypes (v1.2, 2023).</p>
 </div>
 <div class="section level2">
 <h2 id="examples">Examples<a class="anchor" aria-label="anchor" href="#examples"></a>
 </h2>
-<p>These rules can be used to discard impossible bug-drug combinations
+<p>These rules can be used to discard improbable bug-drug combinations
 in your data. For example, <em>Klebsiella</em> produces beta-lactamase
 that prevents ampicillin (or amoxicillin) from working against it. In
 other words, practically every strain of <em>Klebsiella</em> is
 resistant to ampicillin.</p>
 <p>Sometimes, laboratory data can still contain such strains with
-ampicillin being susceptible to ampicillin. This could be because an
-antibiogram is available before an identification is available, and the
-antibiogram is then not re-interpreted based on the identification
-(namely, <em>Klebsiella</em>). EUCAST expert rules solve this, that can
-be applied using <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>:</p>
+<em>Klebsiella</em> being susceptible to ampicillin. This could be
+because an antibiogram is available before an identification is
+available, and the antibiogram is then not re-interpreted based on the
+identification. The <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function resolves this,
+by applying the latest ‘EUCAST Expected Resistant Phenotypes’
+guideline:</p>
 <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">oops</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span></span>
+<code class="sourceCode R"><span><span class="va">oops</span> <span class="op">&lt;-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a></span><span class="op">(</span></span>
 <span>  mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span></span>
-<span>    <span class="st">"Klebsiella"</span>,</span>
-<span>    <span class="st">"Escherichia"</span></span>
+<span>    <span class="st">"Klebsiella pneumoniae"</span>,</span>
+<span>    <span class="st">"Escherichia coli"</span></span>
 <span>  <span class="op">)</span>,</span>
-<span>  ampicillin <span class="op">=</span> <span class="st">"S"</span></span>
+<span>  ampicillin <span class="op">=</span> <span class="fu"><a href="../reference/as.sir.html">as.sir</a></span><span class="op">(</span><span class="st">"S"</span><span class="op">)</span></span>
 <span><span class="op">)</span></span>
 <span><span class="va">oops</span></span>
-<span><span class="co">#&gt;            mo ampicillin</span></span>
-<span><span class="co">#&gt; 1  Klebsiella          S</span></span>
-<span><span class="co">#&gt; 2 Escherichia          S</span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 2 × 2</span></span></span>
+<span><span class="co">#&gt;   mo                    ampicillin</span></span>
+<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                 <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span>     </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> Klebsiella pneumoniae <span style="color: #080808; background-color: #5FD7AF;">  S  </span>     </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> Escherichia coli      <span style="color: #080808; background-color: #5FD7AF;">  S  </span></span></span>
 <span></span>
-<span><span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span><span class="op">(</span><span class="va">oops</span>, info <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span>
-<span><span class="co">#&gt;            mo ampicillin</span></span>
-<span><span class="co">#&gt; 1  Klebsiella          R</span></span>
-<span><span class="co">#&gt; 2 Escherichia          S</span></span></code></pre></div>
+<span><span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span><span class="op">(</span><span class="va">oops</span>, info <span class="op">=</span> <span class="cn">FALSE</span>, overwrite <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 2 × 2</span></span></span>
+<span><span class="co">#&gt;   mo                    ampicillin</span></span>
+<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                 <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span>     </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> Klebsiella pneumoniae <span style="color: #080808; background-color: #FFAFAF;">  R  </span>     </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> Escherichia coli      <span style="color: #080808; background-color: #5FD7AF;">  S  </span></span></span></code></pre></div>
 <p>A more convenient function is
 <code><a href="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code> that uses the same guideline,
 but allows to check for one or more specific microorganisms or
-antibiotics:</p>
+antimicrobials:</p>
 <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span></span>
-<span>  <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>, <span class="st">"Escherichia"</span><span class="op">)</span>,</span>
+<span>  <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Klebsiella pneumoniae"</span>, <span class="st">"Escherichia coli"</span><span class="op">)</span>,</span>
 <span>  <span class="st">"ampicillin"</span></span>
 <span><span class="op">)</span></span>
 <span><span class="co">#&gt; [1]  TRUE FALSE</span></span>
 <span></span>
 <span><span class="fu"><a href="../reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span></span>
-<span>  <span class="st">"Klebsiella"</span>,</span>
+<span>  <span class="st">"Klebsiella pneumoniae"</span>,</span>
 <span>  <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"ampicillin"</span>, <span class="st">"kanamycin"</span><span class="op">)</span></span>
 <span><span class="op">)</span></span>
 <span><span class="co">#&gt; [1]  TRUE FALSE</span></span></code></pre></div>
 <p>EUCAST rules can not only be used for correction, they can also be
 used for filling in known resistance and susceptibility based on results
 of other antimicrobials drugs. This process is called <em>interpretive
-reading</em>, is basically a form of imputation, and is part of the
-<code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function as well:</p>
+reading</em>, and is basically a form of imputation:</p>
 <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span></span>
+<code class="sourceCode R"><span><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a></span><span class="op">(</span></span>
 <span>  mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span></span>
 <span>    <span class="st">"Staphylococcus aureus"</span>,</span>
 <span>    <span class="st">"Enterococcus faecalis"</span>,</span>
@@ -172,8 +177,7 @@ reading</em>, is basically a form of imputation, and is part of the
 <span>  CAZ <span class="op">=</span> <span class="st">"-"</span>, <span class="co"># Ceftazidime</span></span>
 <span>  CXM <span class="op">=</span> <span class="st">"-"</span>, <span class="co"># Cefuroxime</span></span>
 <span>  PEN <span class="op">=</span> <span class="st">"S"</span>, <span class="co"># Benzylenicillin</span></span>
-<span>  FOX <span class="op">=</span> <span class="st">"S"</span>, <span class="co"># Cefoxitin</span></span>
-<span>  stringsAsFactors <span class="op">=</span> <span class="cn">FALSE</span></span>
+<span>  FOX <span class="op">=</span> <span class="st">"S"</span>  <span class="co"># Cefoxitin</span></span>
 <span><span class="op">)</span></span></code></pre></div>
 <div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">data</span></span></code></pre></div>
@@ -242,7 +246,7 @@ reading</em>, is basically a form of imputation, and is part of the
 </tbody>
 </table>
 <div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
+<code class="sourceCode R"><span><span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span><span class="op">(</span><span class="va">data</span>, overwrite <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
 <table class="table">
 <thead><tr class="header">
 <th align="left">mo</th>
@@ -260,7 +264,7 @@ reading</em>, is basically a form of imputation, and is part of the
 <td align="center">-</td>
 <td align="center">S</td>
 <td align="center">R</td>
-<td align="center">S</td>
+<td align="center">R</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
@@ -319,7 +323,7 @@ reading</em>, is basically a form of imputation, and is part of the
 </div>
 
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-  <p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/assets/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/assets/logo_umcg.svg" style="max-width: 150px;"></a></p>
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-<li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
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-<div class="row">
-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.svg" class="logo" alt=""><h1>How to determine multi-drug resistance (MDR)</h1>
-            
-      
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/MDR.Rmd" class="external-link"><code>vignettes/MDR.Rmd</code></a></small>
-      <div class="d-none name"><code>MDR.Rmd</code></div>
-    </div>
-
-    
-    
-<p>With the function <code><a href="../reference/mdro.html">mdro()</a></code>, you can determine which
-micro-organisms are multi-drug resistant organisms (MDRO).</p>
-<div class="section level3">
-<h3 id="type-of-input">Type of input<a class="anchor" aria-label="anchor" href="#type-of-input"></a>
-</h3>
-<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function takes a data set as input, such as a
-regular <code>data.frame</code>. It tries to automatically determine the
-right columns for info about your isolates, such as the name of the
-species and all columns with results of antimicrobial agents. See the
-help page for more info about how to set the right settings for your
-data with the command <code><a href="../reference/mdro.html">?mdro</a></code>.</p>
-<p>For WHONET data (and most other data), all settings are automatically
-set correctly.</p>
-</div>
-<div class="section level3">
-<h3 id="guidelines">Guidelines<a class="anchor" aria-label="anchor" href="#guidelines"></a>
-</h3>
-<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function support multiple guidelines. You can
-select a guideline with the <code>guideline</code> parameter. Currently
-supported guidelines are (case-insensitive):</p>
-<ul>
-<li>
-<p><code>guideline = "CMI2012"</code> (default)</p>
-<p>Magiorakos AP, Srinivasan A <em>et al.</em> “Multidrug-resistant,
-extensively drug-resistant and pandrug-resistant bacteria: an
-international expert proposal for interim standard definitions for
-acquired resistance.” Clinical Microbiology and Infection (2012) (<a href="https://www.clinicalmicrobiologyandinfection.com/article/S1198-743X(14)61632-3/fulltext" class="external-link">link</a>)</p>
-</li>
-<li>
-<p><code>guideline = "EUCAST3.2"</code> (or simply
-<code>guideline = "EUCAST"</code>)</p>
-<p>The European international guideline - EUCAST Expert Rules Version
-3.2 “Intrinsic Resistance and Unusual Phenotypes” (<a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2020/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.2_20200225.pdf" class="external-link">link</a>)</p>
-</li>
-<li>
-<p><code>guideline = "EUCAST3.1"</code></p>
-<p>The European international guideline - EUCAST Expert Rules Version
-3.1 “Intrinsic Resistance and Exceptional Phenotypes Tables” (<a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf" class="external-link">link</a>)</p>
-</li>
-<li>
-<p><code>guideline = "TB"</code></p>
-<p>The international guideline for multi-drug resistant tuberculosis -
-World Health Organization “Companion handbook to the WHO guidelines for
-the programmatic management of drug-resistant tuberculosis” (<a href="https://www.who.int/tb/publications/pmdt_companionhandbook/en/" class="external-link">link</a>)</p>
-</li>
-<li>
-<p><code>guideline = "MRGN"</code></p>
-<p>The German national guideline - Mueller <em>et al.</em> (2015)
-Antimicrobial Resistance and Infection Control 4:7. DOI:
-10.1186/s13756-015-0047-6</p>
-</li>
-<li>
-<p><code>guideline = "BRMO"</code></p>
-<p>The Dutch national guideline - Rijksinstituut voor Volksgezondheid en
-Milieu “WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen)
-(ZKH)” (<a href="https://www.rivm.nl/wip-richtlijn-brmo-bijzonder-resistente-micro-organismen-zkh" class="external-link">link</a>)</p>
-</li>
-</ul>
-<p>Please suggest your own (country-specific) guidelines by letting us
-know: <a href="https://github.com/msberends/AMR/issues/new" class="external-link uri">https://github.com/msberends/AMR/issues/new</a>.</p>
-<div class="section level4">
-<h4 id="custom-guidelines">Custom Guidelines<a class="anchor" aria-label="anchor" href="#custom-guidelines"></a>
-</h4>
-<p>You can also use your own custom guideline. Custom guidelines can be
-set with the <code><a href="../reference/mdro.html">custom_mdro_guideline()</a></code> function. This is of
-great importance if you have custom rules to determine MDROs in your
-hospital, e.g., rules that are dependent on ward, state of contact
-isolation or other variables in your data.</p>
-<p>If you are familiar with <code><a href="https://dplyr.tidyverse.org/reference/case_when.html" class="external-link">case_when()</a></code> of the
-<code>dplyr</code> package, you will recognise the input method to set
-your own rules. Rules must be set using what R considers to be the
-‘formula notation’:</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">custom</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/mdro.html">custom_mdro_guideline</a></span><span class="op">(</span></span>
-<span>  <span class="va">CIP</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">&amp;</span> <span class="va">age</span> <span class="op">&gt;</span> <span class="fl">60</span> <span class="op">~</span> <span class="st">"Elderly Type A"</span>,</span>
-<span>  <span class="va">ERY</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">&amp;</span> <span class="va">age</span> <span class="op">&gt;</span> <span class="fl">60</span> <span class="op">~</span> <span class="st">"Elderly Type B"</span></span>
-<span><span class="op">)</span></span></code></pre></div>
-<p>If a row/an isolate matches the first rule, the value after the first
-<code>~</code> (in this case <em>‘Elderly Type A’</em>) will be set as
-MDRO value. Otherwise, the second rule will be tried and so on. The
-maximum number of rules is unlimited.</p>
-<p>You can print the rules set in the console for an overview. Colours
-will help reading it if your console supports colours.</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">custom</span></span>
-<span><span class="co">#&gt; A set of custom MDRO rules:</span></span>
-<span><span class="co">#&gt;   1. If CIP is "R" and age is higher than 60 then: Elderly Type A</span></span>
-<span><span class="co">#&gt;   2. If ERY is "R" and age is higher than 60 then: Elderly Type B</span></span>
-<span><span class="co">#&gt;   3. Otherwise: Negative</span></span>
-<span><span class="co">#&gt; </span></span>
-<span><span class="co">#&gt; Unmatched rows will return NA.</span></span>
-<span><span class="co">#&gt; Results will be of class 'factor', with ordered levels: Negative &lt; Elderly Type A &lt; Elderly Type B</span></span></code></pre></div>
-<p>The outcome of the function can be used for the
-<code>guideline</code> argument in the <code><a href="../reference/mdro.html">mdro()</a></code> function:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/mdro.html">mdro</a></span><span class="op">(</span><span class="va">example_isolates</span>, guideline <span class="op">=</span> <span class="va">custom</span><span class="op">)</span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/table.html" class="external-link">table</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span>
-<span><span class="co">#&gt; x</span></span>
-<span><span class="co">#&gt;       Negative Elderly Type A Elderly Type B </span></span>
-<span><span class="co">#&gt;           1070            198            732</span></span></code></pre></div>
-<p>The rules set (the <code>custom</code> object in this case) could be
-exported to a shared file location using <code><a href="https://rdrr.io/r/base/readRDS.html" class="external-link">saveRDS()</a></code> if you
-collaborate with multiple users. The custom rules set could then be
-imported using <code><a href="https://rdrr.io/r/base/readRDS.html" class="external-link">readRDS()</a></code>.</p>
-</div>
-</div>
-<div class="section level3">
-<h3 id="examples">Examples<a class="anchor" aria-label="anchor" href="#examples"></a>
-</h3>
-<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function always returns an ordered
-<code>factor</code> for predefined guidelines. For example, the output
-of the default guideline by Magiorakos <em>et al.</em> returns a
-<code>factor</code> with levels ‘Negative’, ‘MDR’, ‘XDR’ or ‘PDR’ in
-that order.</p>
-<p>The next example uses the <code>example_isolates</code> data set.
-This is a data set included with this package and contains full
-antibiograms of 2,000 microbial isolates. It reflects reality and can be
-used to practise AMR data analysis. If we test the MDR/XDR/PDR guideline
-on this data set, we get:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span> <span class="co"># to support pipes: %&gt;%</span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/cleaner/" class="external-link">cleaner</a></span><span class="op">)</span> <span class="co"># to create frequency tables</span></span></code></pre></div>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/mdro.html">mdro</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://msberends.github.io/cleaner/reference/freq.html" class="external-link">freq</a></span><span class="op">(</span><span class="op">)</span> <span class="co"># show frequency table of the result</span></span>
-<span><span class="co">#&gt; Warning: in mdro(): NA introduced for isolates where the available percentage of</span></span>
-<span><span class="co">#&gt; antimicrobial classes was below 50% (set with pct_required_classes)</span></span></code></pre></div>
-<p><strong>Frequency table</strong></p>
-<p>Class: factor &gt; ordered (numeric)<br>
-Length: 2,000<br>
-Levels: 4: Negative &lt; Multi-drug-resistant (MDR) &lt; Extensively
-drug-resistant …<br>
-Available: 1,729 (86.45%, NA: 271 = 13.55%)<br>
-Unique: 2</p>
-<table style="width:100%;" class="table">
-<colgroup>
-<col width="4%">
-<col width="38%">
-<col width="9%">
-<col width="12%">
-<col width="16%">
-<col width="19%">
-</colgroup>
-<thead><tr class="header">
-<th align="left"></th>
-<th align="left">Item</th>
-<th align="right">Count</th>
-<th align="right">Percent</th>
-<th align="right">Cum. Count</th>
-<th align="right">Cum. Percent</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="left">1</td>
-<td align="left">Negative</td>
-<td align="right">1601</td>
-<td align="right">92.6%</td>
-<td align="right">1601</td>
-<td align="right">92.6%</td>
-</tr>
-<tr class="even">
-<td align="left">2</td>
-<td align="left">Multi-drug-resistant (MDR)</td>
-<td align="right">128</td>
-<td align="right">7.4%</td>
-<td align="right">1729</td>
-<td align="right">100.0%</td>
-</tr>
-</tbody>
-</table>
-<p>For another example, I will create a data set to determine multi-drug
-resistant TB:</p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># random_sir() is a helper function to generate</span></span>
-<span><span class="co"># a random vector with values S, I and R</span></span>
-<span><span class="va">my_TB_data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span></span>
-<span>  rifampicin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_sir</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,</span>
-<span>  isoniazid <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_sir</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,</span>
-<span>  gatifloxacin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_sir</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,</span>
-<span>  ethambutol <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_sir</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,</span>
-<span>  pyrazinamide <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_sir</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,</span>
-<span>  moxifloxacin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_sir</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,</span>
-<span>  kanamycin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_sir</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span></span>
-<span><span class="op">)</span></span></code></pre></div>
-<p>Because all column names are automatically verified for valid drug
-names or codes, this would have worked exactly the same way:</p>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">my_TB_data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span></span>
-<span>  RIF <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_sir</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,</span>
-<span>  INH <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_sir</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,</span>
-<span>  GAT <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_sir</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,</span>
-<span>  ETH <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_sir</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,</span>
-<span>  PZA <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_sir</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,</span>
-<span>  MFX <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_sir</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,</span>
-<span>  KAN <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_sir</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span></span>
-<span><span class="op">)</span></span></code></pre></div>
-<p>The data set now looks like this:</p>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">)</span></span>
-<span><span class="co">#&gt;   rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin</span></span>
-<span><span class="co">#&gt; 1          I         R            S          S            S            S</span></span>
-<span><span class="co">#&gt; 2          S         S            I          R            R            S</span></span>
-<span><span class="co">#&gt; 3          R         I            I          I            R            I</span></span>
-<span><span class="co">#&gt; 4          I         S            S          S            S            S</span></span>
-<span><span class="co">#&gt; 5          I         I            I          S            I            S</span></span>
-<span><span class="co">#&gt; 6          R         S            R          S            I            I</span></span>
-<span><span class="co">#&gt;   kanamycin</span></span>
-<span><span class="co">#&gt; 1         R</span></span>
-<span><span class="co">#&gt; 2         I</span></span>
-<span><span class="co">#&gt; 3         S</span></span>
-<span><span class="co">#&gt; 4         I</span></span>
-<span><span class="co">#&gt; 5         I</span></span>
-<span><span class="co">#&gt; 6         I</span></span></code></pre></div>
-<p>We can now add the interpretation of MDR-TB to our data set. You can
-use:</p>
-<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/mdro.html">mdro</a></span><span class="op">(</span><span class="va">my_TB_data</span>, guideline <span class="op">=</span> <span class="st">"TB"</span><span class="op">)</span></span></code></pre></div>
-<p>or its shortcut <code><a href="../reference/mdro.html">mdr_tb()</a></code>:</p>
-<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">my_TB_data</span><span class="op">$</span><span class="va">mdr</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/mdro.html">mdr_tb</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">)</span></span>
-<span><span class="co">#&gt; ℹ No column found as input for col_mo, assuming all rows contain</span></span>
-<span><span class="co">#&gt;   Mycobacterium tuberculosis.</span></span></code></pre></div>
-<p>Create a frequency table of the results:</p>
-<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://msberends.github.io/cleaner/reference/freq.html" class="external-link">freq</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">$</span><span class="va">mdr</span><span class="op">)</span></span></code></pre></div>
-<p><strong>Frequency table</strong></p>
-<p>Class: factor &gt; ordered (numeric)<br>
-Length: 5,000<br>
-Levels: 5: Negative &lt; Mono-resistant &lt; Poly-resistant &lt;
-Multi-drug-resistant &lt;…<br>
-Available: 5,000 (100%, NA: 0 = 0%)<br>
-Unique: 5</p>
-<table style="width:100%;" class="table">
-<colgroup>
-<col width="4%">
-<col width="38%">
-<col width="9%">
-<col width="12%">
-<col width="16%">
-<col width="19%">
-</colgroup>
-<thead><tr class="header">
-<th align="left"></th>
-<th align="left">Item</th>
-<th align="right">Count</th>
-<th align="right">Percent</th>
-<th align="right">Cum. Count</th>
-<th align="right">Cum. Percent</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td align="left">1</td>
-<td align="left">Mono-resistant</td>
-<td align="right">3223</td>
-<td align="right">64.46%</td>
-<td align="right">3223</td>
-<td align="right">64.46%</td>
-</tr>
-<tr class="even">
-<td align="left">2</td>
-<td align="left">Negative</td>
-<td align="right">967</td>
-<td align="right">19.34%</td>
-<td align="right">4190</td>
-<td align="right">83.80%</td>
-</tr>
-<tr class="odd">
-<td align="left">3</td>
-<td align="left">Multi-drug-resistant</td>
-<td align="right">454</td>
-<td align="right">9.08%</td>
-<td align="right">4644</td>
-<td align="right">92.88%</td>
-</tr>
-<tr class="even">
-<td align="left">4</td>
-<td align="left">Poly-resistant</td>
-<td align="right">245</td>
-<td align="right">4.90%</td>
-<td align="right">4889</td>
-<td align="right">97.78%</td>
-</tr>
-<tr class="odd">
-<td align="left">5</td>
-<td align="left">Extensively drug-resistant</td>
-<td align="right">111</td>
-<td align="right">2.22%</td>
-<td align="right">5000</td>
-<td align="right">100.00%</td>
-</tr>
-</tbody>
-</table>
-</div>
-  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
-    </nav></aside>
-</div>
-
-
-
-    <footer><div class="pkgdown-footer-left">
-  <p><code>AMR</code> (for R). Free and open-source, licenced under the <a target="_blank" href="https://github.com/msberends/AMR/blob/main/LICENSE" class="external-link">GNU General Public License version 2.0 (GPL-2)</a>.<br>Developed at the <a target="_blank" href="https://www.rug.nl" class="external-link">University of Groningen</a> and <a target="_blank" href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a> in The Netherlands.</p>
-</div>
-
-<div class="pkgdown-footer-right">
-  <p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/assets/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/assets/logo_umcg.svg" style="max-width: 150px;"></a></p>
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-</html>

articles/PCA.html

@@ -5,21 +5,22 @@
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+<title>Conduct principal component analysis (PCA) for AMR • AMR (for R)</title>
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+<script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.10/font.css" rel="stylesheet">
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-<script src="../extra.js"></script><meta property="og:title" content="How to conduct principal component analysis (PCA) for AMR">
+<script src="../extra.js"></script><meta property="og:title" content="Conduct principal component analysis (PCA) for AMR">
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+<script defer src="https://cdn.jsdelivr.net/npm/katex@0.16.11/dist/katex.min.js" integrity="sha384-7zkQWkzuo3B5mTepMUcHkMB5jZaolc2xDwL6VFqjFALcbeS9Ggm/Yr2r3Dy4lfFg" crossorigin="anonymous"></script><script defer src="https://cdn.jsdelivr.net/npm/katex@0.16.11/dist/contrib/auto-render.min.js" integrity="sha384-43gviWU0YVjaDtb/GhzOouOXtZMP/7XUzwPTstBeZFe/+rCMvRwr4yROQP43s0Xk" crossorigin="anonymous" onload="renderMathInElement(document.body);"></script>
 </head>
 <body>
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@@ -29,7 +30,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9099</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9033</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -43,13 +44,13 @@
   <ul class="dropdown-menu" aria-labelledby="dropdown-how-to">
 <li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
     <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
-    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/AMR_with_tidymodels.html"><span class="fa fa-square-root-variable"></span> Use AMR for Predictive Modelling (tidymodels)</a></li>
     <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
     <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
     <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
-    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../reference/mdro.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
     <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
-    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply EUCAST Rules</a></li>
     <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
     <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
     <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
@@ -60,8 +61,11 @@
 <li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
       </ul>
 <ul class="navbar-nav">
-<li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
-<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
+<li class="nav-item"><form class="form-inline" role="search">
+ <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json">
+</form></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fa-github"></span> Source Code</a></li>
       </ul>
 </div>
 
@@ -74,7 +78,7 @@
 
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.svg" class="logo" alt=""><h1>How to conduct principal component analysis (PCA) for AMR</h1>
+      <img src="../logo.svg" class="logo" alt=""><h1>Conduct principal component analysis (PCA) for AMR</h1>
             
       
       <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/PCA.Rmd" class="external-link"><code>vignettes/PCA.Rmd</code></a></small>
@@ -95,57 +99,57 @@ is currently being developed.</strong></p>
 <p>For PCA, we need to transform our AMR data first. This is what the
 <code>example_isolates</code> data set in this package looks like:</p>
 <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span></span>
+<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://amr-for-r.org">AMR</a></span><span class="op">)</span></span>
 <span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
 <span><span class="fu"><a href="https://pillar.r-lib.org/reference/glimpse.html" class="external-link">glimpse</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span></span>
 <span><span class="co">#&gt; Rows: 2,000</span></span>
 <span><span class="co">#&gt; Columns: 46</span></span>
-<span><span class="co">#&gt; $ date    <span style="color: #949494; font-style: italic;">&lt;date&gt;</span> 2002-01-02, 2002-01-03, 2002-01-07, 2002-01-07, 2002-01-13, 2…</span></span>
-<span><span class="co">#&gt; $ patient <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "A77334", "A77334", "067927", "067927", "067927", "067927", "4…</span></span>
-<span><span class="co">#&gt; $ age     <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> 65, 65, 45, 45, 45, 45, 78, 78, 45, 79, 67, 67, 71, 71, 75, 50…</span></span>
-<span><span class="co">#&gt; $ gender  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "F", "F", "F", "F", "F", "F", "M", "M", "F", "F", "M", "M", "M…</span></span>
-<span><span class="co">#&gt; $ ward    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "Clinical", "Clinical", "ICU", "ICU", "ICU", "ICU", "Clinical"…</span></span>
-<span><span class="co">#&gt; $ mo      <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span> "B_ESCHR_COLI", "B_ESCHR_COLI", "B_STPHY_EPDR", "B_STPHY_EPDR",…</span></span>
-<span><span class="co">#&gt; $ PEN     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, S,…</span></span>
-<span><span class="co">#&gt; $ OXA     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
-<span><span class="co">#&gt; $ FLC     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, R, R, R, R, S, S, R, S, S, S, NA, NA, NA, NA, NA, R, R…</span></span>
-<span><span class="co">#&gt; $ AMX     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, R, R, NA, NA, NA, NA, NA, NA, R, NA, N…</span></span>
-<span><span class="co">#&gt; $ AMC     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> I, I, NA, NA, NA, NA, S, S, NA, NA, S, S, I, I, R, I, I, NA, N…</span></span>
-<span><span class="co">#&gt; $ AMP     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, R, R, NA, NA, NA, NA, NA, NA, R, NA, N…</span></span>
-<span><span class="co">#&gt; $ TZP     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
-<span><span class="co">#&gt; $ CZO     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, NA,…</span></span>
-<span><span class="co">#&gt; $ FEP     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
-<span><span class="co">#&gt; $ CXM     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> I, I, R, R, R, R, S, S, R, S, S, S, S, S, NA, S, S, R, R, S, S…</span></span>
-<span><span class="co">#&gt; $ FOX     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, NA,…</span></span>
-<span><span class="co">#&gt; $ CTX     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, S, S…</span></span>
-<span><span class="co">#&gt; $ CAZ     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, R, R, R, R, R, R, R, R, R, R, NA, NA, NA, S, S, R, R, …</span></span>
-<span><span class="co">#&gt; $ CRO     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, S, S…</span></span>
-<span><span class="co">#&gt; $ GEN     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
-<span><span class="co">#&gt; $ TOB     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, S, S, NA, NA, NA, NA, S, S, NA, NA, NA…</span></span>
-<span><span class="co">#&gt; $ AMK     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
-<span><span class="co">#&gt; $ KAN     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
-<span><span class="co">#&gt; $ TMP     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, S, S, R, R, R, R, S, S, NA, NA, S, S, S, S, S, R, R, R, …</span></span>
-<span><span class="co">#&gt; $ SXT     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, S, S, NA, NA, NA, NA, S, S, NA, NA, S, S, S, S, S, NA, N…</span></span>
-<span><span class="co">#&gt; $ NIT     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R,…</span></span>
-<span><span class="co">#&gt; $ FOS     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
-<span><span class="co">#&gt; $ LNZ     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R, R, R, N…</span></span>
-<span><span class="co">#&gt; $ CIP     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, NA, NA, NA, NA, S, S…</span></span>
-<span><span class="co">#&gt; $ MFX     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
-<span><span class="co">#&gt; $ VAN     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, S, S, S, S, S, S, S, S, NA, NA, R, R, R, R, R, S, S, S, …</span></span>
-<span><span class="co">#&gt; $ TEC     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R, R, R, N…</span></span>
-<span><span class="co">#&gt; $ TCY     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, S, S, S, S, S, S, S, I, S, S, NA, NA, I, R, R, S, I, R, …</span></span>
-<span><span class="co">#&gt; $ TGC     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, S, S, S, S, S, S, S, NA, S, S, NA, NA, NA, R, R, S, NA…</span></span>
-<span><span class="co">#&gt; $ DOX     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, S, S, S, S, S, S, S, NA, S, S, NA, NA, NA, R, R, S, NA…</span></span>
-<span><span class="co">#&gt; $ ERY     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, R, R, R, R, S, S, R, S, S, S, R, R, R, R, R, R, R, R, S,…</span></span>
-<span><span class="co">#&gt; $ CLI     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, NA, NA, NA, R, NA, NA, NA, NA, NA, NA, R, R, R, R, R, NA…</span></span>
-<span><span class="co">#&gt; $ AZM     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, R, R, R, R, S, S, R, S, S, S, R, R, R, R, R, R, R, R, S,…</span></span>
-<span><span class="co">#&gt; $ IPM     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, S, S…</span></span>
-<span><span class="co">#&gt; $ MEM     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
-<span><span class="co">#&gt; $ MTR     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
-<span><span class="co">#&gt; $ CHL     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
-<span><span class="co">#&gt; $ COL     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, R, R, R, R, R, R, R, R, R, R, NA, NA, NA, R, R, R, R, …</span></span>
-<span><span class="co">#&gt; $ MUP     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
-<span><span class="co">#&gt; $ RIF     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R, R, R, N…</span></span></code></pre></div>
+<span><span class="co">#&gt; $ date    <span style="color: #949494; font-style: italic;">&lt;date&gt;</span> 2002-01-02<span style="color: #949494;">, </span>2002-01-03<span style="color: #949494;">, </span>2002-01-07<span style="color: #949494;">, </span>2002-01-07<span style="color: #949494;">, </span>2002-01-13<span style="color: #949494;">, </span>2…</span></span>
+<span><span class="co">#&gt; $ patient <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "A77334"<span style="color: #949494;">, </span>"A77334"<span style="color: #949494;">, </span>"067927"<span style="color: #949494;">, </span>"067927"<span style="color: #949494;">, </span>"067927"<span style="color: #949494;">, </span>"067927"<span style="color: #949494;">, </span>"4…</span></span>
+<span><span class="co">#&gt; $ age     <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> 65<span style="color: #949494;">, </span>65<span style="color: #949494;">, </span>45<span style="color: #949494;">, </span>45<span style="color: #949494;">, </span>45<span style="color: #949494;">, </span>45<span style="color: #949494;">, </span>78<span style="color: #949494;">, </span>78<span style="color: #949494;">, </span>45<span style="color: #949494;">, </span>79<span style="color: #949494;">, </span>67<span style="color: #949494;">, </span>67<span style="color: #949494;">, </span>71<span style="color: #949494;">, </span>71<span style="color: #949494;">, </span>75<span style="color: #949494;">, </span>50…</span></span>
+<span><span class="co">#&gt; $ gender  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "F"<span style="color: #949494;">, </span>"F"<span style="color: #949494;">, </span>"F"<span style="color: #949494;">, </span>"F"<span style="color: #949494;">, </span>"F"<span style="color: #949494;">, </span>"F"<span style="color: #949494;">, </span>"M"<span style="color: #949494;">, </span>"M"<span style="color: #949494;">, </span>"F"<span style="color: #949494;">, </span>"F"<span style="color: #949494;">, </span>"M"<span style="color: #949494;">, </span>"M"<span style="color: #949494;">, </span>"M…</span></span>
+<span><span class="co">#&gt; $ ward    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "Clinical"<span style="color: #949494;">, </span>"Clinical"<span style="color: #949494;">, </span>"ICU"<span style="color: #949494;">, </span>"ICU"<span style="color: #949494;">, </span>"ICU"<span style="color: #949494;">, </span>"ICU"<span style="color: #949494;">, </span>"Clinical"…</span></span>
+<span><span class="co">#&gt; $ mo      <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span> "B_ESCHR_COLI"<span style="color: #949494;">, </span>"B_ESCHR_COLI"<span style="color: #949494;">, </span>"B_STPHY_EPDR"<span style="color: #949494;">, </span>"B_STPHY_EPDR"<span style="color: #949494;">,</span>…</span></span>
+<span><span class="co">#&gt; $ PEN     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">,</span>…</span></span>
+<span><span class="co">#&gt; $ OXA     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span>…</span></span>
+<span><span class="co">#&gt; $ FLC     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R…</span></span>
+<span><span class="co">#&gt; $ AMX     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">N</span>…</span></span>
+<span><span class="co">#&gt; $ AMC     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> I<span style="color: #949494;">, </span>I<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>I<span style="color: #949494;">, </span>I<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>I<span style="color: #949494;">, </span>I<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">N</span>…</span></span>
+<span><span class="co">#&gt; $ AMP     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">N</span>…</span></span>
+<span><span class="co">#&gt; $ TZP     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span>…</span></span>
+<span><span class="co">#&gt; $ CZO     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">,</span>…</span></span>
+<span><span class="co">#&gt; $ FEP     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span>…</span></span>
+<span><span class="co">#&gt; $ CXM     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> I<span style="color: #949494;">, </span>I<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S…</span></span>
+<span><span class="co">#&gt; $ FOX     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">,</span>…</span></span>
+<span><span class="co">#&gt; $ CTX     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S…</span></span>
+<span><span class="co">#&gt; $ CAZ     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>…</span></span>
+<span><span class="co">#&gt; $ CRO     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S…</span></span>
+<span><span class="co">#&gt; $ GEN     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span>…</span></span>
+<span><span class="co">#&gt; $ TOB     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span>…</span></span>
+<span><span class="co">#&gt; $ AMK     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span>…</span></span>
+<span><span class="co">#&gt; $ KAN     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span>…</span></span>
+<span><span class="co">#&gt; $ TMP     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>…</span></span>
+<span><span class="co">#&gt; $ SXT     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">N</span>…</span></span>
+<span><span class="co">#&gt; $ NIT     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">,</span>…</span></span>
+<span><span class="co">#&gt; $ FOS     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span>…</span></span>
+<span><span class="co">#&gt; $ LNZ     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span><span style="color: #BB0000;">N</span>…</span></span>
+<span><span class="co">#&gt; $ CIP     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S…</span></span>
+<span><span class="co">#&gt; $ MFX     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span>…</span></span>
+<span><span class="co">#&gt; $ VAN     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>…</span></span>
+<span><span class="co">#&gt; $ TEC     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span><span style="color: #BB0000;">N</span>…</span></span>
+<span><span class="co">#&gt; $ TCY     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>I<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>I<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>I<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>…</span></span>
+<span><span class="co">#&gt; $ TGC     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span>…</span></span>
+<span><span class="co">#&gt; $ DOX     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span>…</span></span>
+<span><span class="co">#&gt; $ ERY     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">,</span>…</span></span>
+<span><span class="co">#&gt; $ CLI     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span>…</span></span>
+<span><span class="co">#&gt; $ AZM     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>S<span style="color: #949494;">,</span>…</span></span>
+<span><span class="co">#&gt; $ IPM     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>S<span style="color: #949494;">, </span>S…</span></span>
+<span><span class="co">#&gt; $ MEM     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span>…</span></span>
+<span><span class="co">#&gt; $ MTR     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span>…</span></span>
+<span><span class="co">#&gt; $ CHL     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span>…</span></span>
+<span><span class="co">#&gt; $ COL     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>…</span></span>
+<span><span class="co">#&gt; $ MUP     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span>…</span></span>
+<span><span class="co">#&gt; $ RIF     <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span><span style="color: #BB0000;">NA</span><span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span>R<span style="color: #949494;">, </span><span style="color: #BB0000;">N</span>…</span></span></code></pre></div>
 <p>Now to transform this to a data set with only resistance percentages
 per taxonomic order and genus:</p>
 <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
@@ -180,8 +184,8 @@ that contain numeric values in all selected variables, so we now only
 need to do:</p>
 <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">pca_result</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/pca.html">pca</a></span><span class="op">(</span><span class="va">resistance_data</span><span class="op">)</span></span>
-<span><span class="co">#&gt; ℹ Columns selected for PCA: "AMC", "CAZ", "CTX", "CXM", "GEN", "SXT",</span></span>
-<span><span class="co">#&gt;   "TMP", and "TOB". Total observations available: 7.</span></span></code></pre></div>
+<span><span class="co">#&gt; <span style="color: #0000BB;">ℹ Columns selected for PCA: "</span><span style="color: #0000BB; font-weight: bold;">AMC</span><span style="color: #0000BB;">", "</span><span style="color: #0000BB; font-weight: bold;">CAZ</span><span style="color: #0000BB;">", "</span><span style="color: #0000BB; font-weight: bold;">CTX</span><span style="color: #0000BB;">", "</span><span style="color: #0000BB; font-weight: bold;">CXM</span><span style="color: #0000BB;">", "</span><span style="color: #0000BB; font-weight: bold;">GEN</span><span style="color: #0000BB;">", "</span><span style="color: #0000BB; font-weight: bold;">SXT</span><span style="color: #0000BB;">",</span></span></span>
+<span><span class="co"><span style="color: #0000BB;">#&gt;   "</span><span style="color: #0000BB; font-weight: bold;">TMP</span><span style="color: #0000BB;">", and "</span><span style="color: #0000BB; font-weight: bold;">TOB</span><span style="color: #0000BB;">". Total observations available: 7.</span></span></span></code></pre></div>
 <p>The result can be reviewed with the good old <code><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary()</a></code>
 function:</p>
 <div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
@@ -230,7 +234,7 @@ automatically adds the right labels and even groups:</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/assets/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/assets/logo_umcg.svg" style="max-width: 150px;"></a></p>
+  <p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://amr-for-r.org/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://amr-for-r.org/logo_umcg.svg" style="max-width: 150px;"></a></p>
 </div>
 
     </footer>

articles/WHONET.html

@@ -5,21 +5,22 @@
 <meta charset="utf-8">
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
-<title>How to work with WHONET data • AMR (for R)</title>
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-<script src="../extra.js"></script><meta property="og:title" content="How to work with WHONET data">
+<script src="../extra.js"></script><meta property="og:title" content="Work with WHONET data">
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+<script defer src="https://cdn.jsdelivr.net/npm/katex@0.16.11/dist/katex.min.js" integrity="sha384-7zkQWkzuo3B5mTepMUcHkMB5jZaolc2xDwL6VFqjFALcbeS9Ggm/Yr2r3Dy4lfFg" crossorigin="anonymous"></script><script defer src="https://cdn.jsdelivr.net/npm/katex@0.16.11/dist/contrib/auto-render.min.js" integrity="sha384-43gviWU0YVjaDtb/GhzOouOXtZMP/7XUzwPTstBeZFe/+rCMvRwr4yROQP43s0Xk" crossorigin="anonymous" onload="renderMathInElement(document.body);"></script>
 </head>
 <body>
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@@ -29,7 +30,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9099</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9033</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -43,13 +44,13 @@
   <ul class="dropdown-menu" aria-labelledby="dropdown-how-to">
 <li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
     <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
-    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/AMR_with_tidymodels.html"><span class="fa fa-square-root-variable"></span> Use AMR for Predictive Modelling (tidymodels)</a></li>
     <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
     <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
     <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
-    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../reference/mdro.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
     <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
-    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply EUCAST Rules</a></li>
     <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
     <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
     <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
@@ -60,8 +61,11 @@
 <li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
       </ul>
 <ul class="navbar-nav">
-<li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
-<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
+<li class="nav-item"><form class="form-inline" role="search">
+ <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json">
+</form></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fa-github"></span> Source Code</a></li>
       </ul>
 </div>
 
@@ -74,7 +78,7 @@
 
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.svg" class="logo" alt=""><h1>How to work with WHONET data</h1>
+      <img src="../logo.svg" class="logo" alt=""><h1>Work with WHONET data</h1>
             
       
       <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/WHONET.Rmd" class="external-link"><code>vignettes/WHONET.Rmd</code></a></small>
@@ -96,8 +100,8 @@ correctly.</p>
 <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://readxl.tidyverse.org" class="external-link">readxl</a></span><span class="op">)</span></span>
 <span><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://readxl.tidyverse.org/reference/read_excel.html" class="external-link">read_excel</a></span><span class="op">(</span>path <span class="op">=</span> <span class="st">"path/to/your/file.xlsx"</span><span class="op">)</span></span></code></pre></div>
-<p>This package comes with an <a href="https://msberends.github.io/AMR/reference/WHONET.html">example
-data set <code>WHONET</code></a>. We will use it for this analysis.</p>
+<p>This package comes with an <a href="https://amr-for-r.org/reference/WHONET.html">example data set
+<code>WHONET</code></a>. We will use it for this analysis.</p>
 </div>
 <div class="section level3">
 <h3 id="preparation">Preparation<a class="anchor" aria-label="anchor" href="#preparation"></a>
@@ -108,14 +112,14 @@ yet, I suggest you read about it on their website: <a href="https://www.tidyvers
 <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span> <span class="co"># part of tidyverse</span></span>
 <span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span> <span class="co"># part of tidyverse</span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span> <span class="co"># this package</span></span>
+<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://amr-for-r.org">AMR</a></span><span class="op">)</span> <span class="co"># this package</span></span>
 <span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/cleaner/" class="external-link">cleaner</a></span><span class="op">)</span> <span class="co"># to create frequency tables</span></span></code></pre></div>
 <p>We will have to transform some variables to simplify and automate the
 analysis:</p>
 <ul>
 <li>Microorganisms should be transformed to our own microorganism codes
-(called an <code>mo</code>) using <a href="https://msberends.github.io/AMR/reference/catalogue_of_life">our
-Catalogue of Life reference data set</a>, which contains all ~70,000
+(called an <code>mo</code>) using <a href="https://amr-for-r.org/reference/catalogue_of_life">our Catalogue
+of Life reference data set</a>, which contains all ~70,000
 microorganisms from the taxonomic kingdoms Bacteria, Fungi and Protozoa.
 We do the tranformation with <code><a href="../reference/as.mo.html">as.mo()</a></code>. This function also
 recognises almost all WHONET abbreviations of microorganisms.</li>
@@ -257,7 +261,7 @@ Length: 500<br>
 Levels: 5: S &lt; SDD &lt; I &lt; R &lt; NI<br>
 Available: 481 (96.2%, NA: 19 = 3.8%)<br>
 Unique: 3</p>
-<p>Drug: Amoxicillin/clavulanic acid (AMC, J01CR02)<br>
+<p>Drug: Amoxicillin/clavulanic acid (AMC, J01CR02/QJ01CR02)<br>
 Drug group: Beta-lactams/penicillins<br>
 %SI: 78.59%</p>
 <table class="table">
@@ -320,7 +324,7 @@ using the included <code><a href="../reference/ggplot_sir.html">ggplot_sir()</a>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/assets/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/assets/logo_umcg.svg" style="max-width: 150px;"></a></p>
+  <p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://amr-for-r.org/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://amr-for-r.org/logo_umcg.svg" style="max-width: 150px;"></a></p>
 </div>
 
     </footer>

articles/WISCA.html

@@ -0,0 +1,464 @@
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en">
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+<title>Estimating Empirical Coverage with WISCA • AMR (for R)</title>
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+<script src="../extra.js"></script><meta property="og:title" content="Estimating Empirical Coverage with WISCA">
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+    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
+
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9033</small>
+
+
+    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
+      <span class="navbar-toggler-icon"></span>
+    </button>
+
+    <div id="navbar" class="collapse navbar-collapse ms-3">
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+<li class="nav-item dropdown">
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to">
+<li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/AMR_with_tidymodels.html"><span class="fa fa-square-root-variable"></span> Use AMR for Predictive Modelling (tidymodels)</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../reference/mdro.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply EUCAST Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul>
+</li>
+<li class="nav-item"><a class="nav-link" href="../articles/AMR_for_Python.html"><span class="fa fab fa-python"></span> AMR for Python</a></li>
+<li class="nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul>
+<ul class="navbar-nav">
+<li class="nav-item"><form class="form-inline" role="search">
+ <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json">
+</form></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fa-github"></span> Source Code</a></li>
+      </ul>
+</div>
+
+
+  </div>
+</nav><div class="container template-article">
+
+
+
+
+<div class="row">
+  <main id="main" class="col-md-9"><div class="page-header">
+      <img src="../logo.svg" class="logo" alt=""><h1>Estimating Empirical Coverage with WISCA</h1>
+            
+      
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/WISCA.Rmd" class="external-link"><code>vignettes/WISCA.Rmd</code></a></small>
+      <div class="d-none name"><code>WISCA.Rmd</code></div>
+    </div>
+
+    
+    
+<blockquote>
+<p>This explainer was largely written by our <a href="https://chat.amr-for-r.org" class="external-link">AMR for R Assistant</a>, a ChatGPT
+manually-trained model able to answer any question about the
+<code>AMR</code> package.</p>
+</blockquote>
+<div class="section level2">
+<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
+</h2>
+<p>Clinical guidelines for empirical antimicrobial therapy require
+<em>probabilistic reasoning</em>: what is the chance that a regimen will
+cover the likely infecting organisms, before culture results are
+available?</p>
+<p>This is the purpose of <strong>WISCA</strong>, or
+<strong>Weighted-Incidence Syndromic Combination
+Antibiogram</strong>.</p>
+<p>WISCA is a Bayesian approach that integrates:</p>
+<ul>
+<li>
+<strong>Pathogen prevalence</strong> (how often each species causes
+the syndrome),</li>
+<li>
+<strong>Regimen susceptibility</strong> (how often a regimen works
+<em>if</em> the pathogen is known),</li>
+</ul>
+<p>to estimate the <strong>overall empirical coverage</strong> of
+antimicrobial regimens, with quantified uncertainty.</p>
+<p>This vignette explains how WISCA works, why it is useful, and how to
+apply it using the <code>AMR</code> package.</p>
+</div>
+<div class="section level2">
+<h2 id="why-traditional-antibiograms-fall-short">Why traditional antibiograms fall short<a class="anchor" aria-label="anchor" href="#why-traditional-antibiograms-fall-short"></a>
+</h2>
+<p>A standard antibiogram gives you:</p>
+<pre><code>Species → Antibiotic → Susceptibility %</code></pre>
+<p>But clinicians don’t know the species <em>a priori</em>. They need to
+choose a regimen that covers the <strong>likely pathogens</strong>,
+without knowing which one is present.</p>
+<p>Traditional antibiograms calculate the susceptibility % as just the
+number of resistant isolates divided by the total number of tested
+isolates. Therefore, traditional antibiograms:</p>
+<ul>
+<li>Fragment information by organism,</li>
+<li>Do not weight by real-world prevalence,</li>
+<li>Do not account for combination therapy or sample size,</li>
+<li>Do not provide uncertainty.</li>
+</ul>
+</div>
+<div class="section level2">
+<h2 id="the-idea-of-wisca">The idea of WISCA<a class="anchor" aria-label="anchor" href="#the-idea-of-wisca"></a>
+</h2>
+<p>WISCA asks:</p>
+<blockquote>
+<p>“What is the <strong>probability</strong> that this regimen
+<strong>will cover</strong> the pathogen, given the syndrome?”</p>
+</blockquote>
+<p>This means combining two things:</p>
+<ul>
+<li>
+<strong>Incidence</strong> of each pathogen in the syndrome,</li>
+<li>
+<strong>Susceptibility</strong> of each pathogen to the
+regimen.</li>
+</ul>
+<p>We can write this as:</p>
+<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mtext mathvariant="normal">Coverage</mtext><mo>=</mo><munder><mo>∑</mo><mi>i</mi></munder><mrow><mo stretchy="true" form="prefix">(</mo><msub><mtext mathvariant="normal">Incidence</mtext><mi>i</mi></msub><mo>×</mo><msub><mtext mathvariant="normal">Susceptibility</mtext><mi>i</mi></msub><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">\text{Coverage} = \sum_i (\text{Incidence}_i \times \text{Susceptibility}_i)</annotation></semantics></math></p>
+<p>For example, suppose:</p>
+<ul>
+<li>
+<em>E. coli</em> causes 60% of cases, and 90% of <em>E. coli</em>
+are susceptible to a drug.</li>
+<li>
+<em>Klebsiella</em> causes 40% of cases, and 70% of
+<em>Klebsiella</em> are susceptible.</li>
+</ul>
+<p>Then:</p>
+<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mtext mathvariant="normal">Coverage</mtext><mo>=</mo><mrow><mo stretchy="true" form="prefix">(</mo><mn>0.6</mn><mo>×</mo><mn>0.9</mn><mo stretchy="true" form="postfix">)</mo></mrow><mo>+</mo><mrow><mo stretchy="true" form="prefix">(</mo><mn>0.4</mn><mo>×</mo><mn>0.7</mn><mo stretchy="true" form="postfix">)</mo></mrow><mo>=</mo><mn>0.82</mn></mrow><annotation encoding="application/x-tex">\text{Coverage} = (0.6 \times 0.9) + (0.4 \times 0.7) = 0.82</annotation></semantics></math></p>
+<p>But in real data, incidence and susceptibility are <strong>estimated
+from samples</strong>, so they carry uncertainty. WISCA models this
+<strong>probabilistically</strong>, using conjugate Bayesian
+distributions.</p>
+</div>
+<div class="section level2">
+<h2 id="the-bayesian-engine-behind-wisca">The Bayesian engine behind WISCA<a class="anchor" aria-label="anchor" href="#the-bayesian-engine-behind-wisca"></a>
+</h2>
+<div class="section level3">
+<h3 id="pathogen-incidence">Pathogen incidence<a class="anchor" aria-label="anchor" href="#pathogen-incidence"></a>
+</h3>
+<p>Let:</p>
+<ul>
+<li>
+<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>K</mi><annotation encoding="application/x-tex">K</annotation></semantics></math>
+be the number of pathogens,</li>
+<li>
+<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>α</mi><mo>=</mo><mrow><mo stretchy="true" form="prefix">(</mo><mn>1</mn><mo>,</mo><mn>1</mn><mo>,</mo><mi>…</mi><mo>,</mo><mn>1</mn><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">\alpha = (1, 1, \ldots, 1)</annotation></semantics></math>
+be a <strong>Dirichlet</strong> prior (uniform),</li>
+<li>
+<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>n</mi><mo>=</mo><mrow><mo stretchy="true" form="prefix">(</mo><msub><mi>n</mi><mn>1</mn></msub><mo>,</mo><mi>…</mi><mo>,</mo><msub><mi>n</mi><mi>K</mi></msub><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">n = (n_1, \ldots, n_K)</annotation></semantics></math>
+be the observed counts per species.</li>
+</ul>
+<p>Then the posterior incidence is:</p>
+<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>p</mi><mo>∼</mo><mtext mathvariant="normal">Dirichlet</mtext><mrow><mo stretchy="true" form="prefix">(</mo><msub><mi>α</mi><mn>1</mn></msub><mo>+</mo><msub><mi>n</mi><mn>1</mn></msub><mo>,</mo><mi>…</mi><mo>,</mo><msub><mi>α</mi><mi>K</mi></msub><mo>+</mo><msub><mi>n</mi><mi>K</mi></msub><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">p \sim \text{Dirichlet}(\alpha_1 + n_1, \ldots, \alpha_K + n_K)</annotation></semantics></math></p>
+<p>To simulate from this, we use:</p>
+<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>x</mi><mi>i</mi></msub><mo>∼</mo><mtext mathvariant="normal">Gamma</mtext><mrow><mo stretchy="true" form="prefix">(</mo><msub><mi>α</mi><mi>i</mi></msub><mo>+</mo><msub><mi>n</mi><mi>i</mi></msub><mo>,</mo><mspace width="0.222em"></mspace><mn>1</mn><mo stretchy="true" form="postfix">)</mo></mrow><mo>,</mo><mspace width="1.0em"></mspace><msub><mi>p</mi><mi>i</mi></msub><mo>=</mo><mfrac><msub><mi>x</mi><mi>i</mi></msub><mrow><munderover><mo>∑</mo><mrow><mi>j</mi><mo>=</mo><mn>1</mn></mrow><mi>K</mi></munderover><msub><mi>x</mi><mi>j</mi></msub></mrow></mfrac></mrow><annotation encoding="application/x-tex">x_i \sim \text{Gamma}(\alpha_i + n_i,\ 1), \quad p_i = \frac{x_i}{\sum_{j=1}^{K} x_j}</annotation></semantics></math></p>
+</div>
+<div class="section level3">
+<h3 id="susceptibility">Susceptibility<a class="anchor" aria-label="anchor" href="#susceptibility"></a>
+</h3>
+<p>Each pathogen–regimen pair has a prior and data:</p>
+<ul>
+<li>Prior:
+<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mtext mathvariant="normal">Beta</mtext><mrow><mo stretchy="true" form="prefix">(</mo><msub><mi>α</mi><mn>0</mn></msub><mo>,</mo><msub><mi>β</mi><mn>0</mn></msub><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">\text{Beta}(\alpha_0, \beta_0)</annotation></semantics></math>,
+with default
+<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>α</mi><mn>0</mn></msub><mo>=</mo><msub><mi>β</mi><mn>0</mn></msub><mo>=</mo><mn>1</mn></mrow><annotation encoding="application/x-tex">\alpha_0 = \beta_0 = 1</annotation></semantics></math>
+</li>
+<li>Data:
+<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>S</mi><annotation encoding="application/x-tex">S</annotation></semantics></math>
+susceptible out of
+<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>N</mi><annotation encoding="application/x-tex">N</annotation></semantics></math>
+tested</li>
+</ul>
+<p>The
+<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi>S</mi><annotation encoding="application/x-tex">S</annotation></semantics></math>
+category could also include values SDD (susceptible, dose-dependent) and
+I (intermediate [CLSI], or susceptible, increased exposure
+[EUCAST]).</p>
+<p>Then the posterior is:</p>
+<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>θ</mi><mo>∼</mo><mtext mathvariant="normal">Beta</mtext><mrow><mo stretchy="true" form="prefix">(</mo><msub><mi>α</mi><mn>0</mn></msub><mo>+</mo><mi>S</mi><mo>,</mo><mspace width="0.222em"></mspace><msub><mi>β</mi><mn>0</mn></msub><mo>+</mo><mi>N</mi><mo>−</mo><mi>S</mi><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">\theta \sim \text{Beta}(\alpha_0 + S,\ \beta_0 + N - S)</annotation></semantics></math></p>
+</div>
+<div class="section level3">
+<h3 id="final-coverage-estimate">Final coverage estimate<a class="anchor" aria-label="anchor" href="#final-coverage-estimate"></a>
+</h3>
+<p>Putting it together:</p>
+<ol style="list-style-type: decimal">
+<li>Simulate pathogen incidence:
+<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>𝐩</mi><mo>∼</mo><mtext mathvariant="normal">Dirichlet</mtext></mrow><annotation encoding="application/x-tex">\boldsymbol{p} \sim \text{Dirichlet}</annotation></semantics></math>
+</li>
+<li>Simulate susceptibility:
+<math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>θ</mi><mi>i</mi></msub><mo>∼</mo><mtext mathvariant="normal">Beta</mtext><mrow><mo stretchy="true" form="prefix">(</mo><mn>1</mn><mo>+</mo><msub><mi>S</mi><mi>i</mi></msub><mo>,</mo><mspace width="0.222em"></mspace><mn>1</mn><mo>+</mo><msub><mi>R</mi><mi>i</mi></msub><mo stretchy="true" form="postfix">)</mo></mrow></mrow><annotation encoding="application/x-tex">\theta_i \sim \text{Beta}(1 + S_i,\ 1 + R_i)</annotation></semantics></math>
+</li>
+<li>Combine:</li>
+</ol>
+<p><math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mtext mathvariant="normal">Coverage</mtext><mo>=</mo><munderover><mo>∑</mo><mrow><mi>i</mi><mo>=</mo><mn>1</mn></mrow><mi>K</mi></munderover><msub><mi>p</mi><mi>i</mi></msub><mo>⋅</mo><msub><mi>θ</mi><mi>i</mi></msub></mrow><annotation encoding="application/x-tex">\text{Coverage} = \sum_{i=1}^{K} p_i \cdot \theta_i</annotation></semantics></math></p>
+<p>Repeat this simulation (e.g. 1000×) and summarise:</p>
+<ul>
+<li>
+<strong>Mean</strong> = expected coverage</li>
+<li>
+<strong>Quantiles</strong> = credible interval</li>
+</ul>
+</div>
+</div>
+<div class="section level2">
+<h2 id="practical-use-in-the-amr-package">Practical use in the <code>AMR</code> package<a class="anchor" aria-label="anchor" href="#practical-use-in-the-amr-package"></a>
+</h2>
+<div class="section level3">
+<h3 id="prepare-data-and-simulate-synthetic-syndrome">Prepare data and simulate synthetic syndrome<a class="anchor" aria-label="anchor" href="#prepare-data-and-simulate-synthetic-syndrome"></a>
+</h3>
+<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://amr-for-r.org">AMR</a></span><span class="op">)</span></span>
+<span><span class="va">data</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span></span>
+<span></span>
+<span><span class="co"># Structure of our data</span></span>
+<span><span class="va">data</span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 2,000 × 46</span></span></span>
+<span><span class="co">#&gt;    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX  </span></span>
+<span><span class="co">#&gt;    <span style="color: #949494; font-style: italic;">&lt;date&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span></span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 1</span> 2002-01-02 A77334     65 F      Clinical <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #B2B2B2;">  NA</span>  <span style="color: #B2B2B2;">  NA</span> </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 2</span> 2002-01-03 A77334     65 F      Clinical <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #B2B2B2;">  NA</span>  <span style="color: #B2B2B2;">  NA</span> </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 3</span> 2002-01-07 067927     45 F      ICU      <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>EPDR <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span> </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 4</span> 2002-01-07 067927     45 F      ICU      <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>EPDR <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span> </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 5</span> 2002-01-13 067927     45 F      ICU      <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>EPDR <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span> </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 6</span> 2002-01-13 067927     45 F      ICU      <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>EPDR <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span> </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 7</span> 2002-01-14 462729     78 M      Clinical <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>AURS <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #080808; background-color: #5FD7AF;">  S  </span> <span style="color: #080808; background-color: #FFAFAF;">  R  </span></span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> 2002-01-14 462729     78 M      Clinical <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>AURS <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #080808; background-color: #5FD7AF;">  S  </span> <span style="color: #080808; background-color: #FFAFAF;">  R  </span></span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> 2002-01-16 067927     45 F      ICU      <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>EPDR <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span> </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> 2002-01-17 858515     79 F      ICU      <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>EPDR <span style="color: #080808; background-color: #FFAFAF;">  R  </span> <span style="color: #B2B2B2;">  NA</span>  <span style="color: #080808; background-color: #5FD7AF;">  S  </span> <span style="color: #B2B2B2;">  NA</span> </span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 1,990 more rows</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 36 more variables: AMC &lt;sir&gt;, AMP &lt;sir&gt;, TZP &lt;sir&gt;, CZO &lt;sir&gt;, FEP &lt;sir&gt;,</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;">#   CXM &lt;sir&gt;, FOX &lt;sir&gt;, CTX &lt;sir&gt;, CAZ &lt;sir&gt;, CRO &lt;sir&gt;, GEN &lt;sir&gt;,</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;">#   TOB &lt;sir&gt;, AMK &lt;sir&gt;, KAN &lt;sir&gt;, TMP &lt;sir&gt;, SXT &lt;sir&gt;, NIT &lt;sir&gt;,</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;">#   FOS &lt;sir&gt;, LNZ &lt;sir&gt;, CIP &lt;sir&gt;, MFX &lt;sir&gt;, VAN &lt;sir&gt;, TEC &lt;sir&gt;,</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;">#   TCY &lt;sir&gt;, TGC &lt;sir&gt;, DOX &lt;sir&gt;, ERY &lt;sir&gt;, CLI &lt;sir&gt;, AZM &lt;sir&gt;,</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;">#   IPM &lt;sir&gt;, MEM &lt;sir&gt;, MTR &lt;sir&gt;, CHL &lt;sir&gt;, COL &lt;sir&gt;, MUP &lt;sir&gt;, …</span></span></span>
+<span></span>
+<span><span class="co"># Add a fake syndrome column</span></span>
+<span><span class="va">data</span><span class="op">$</span><span class="va">syndrome</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse</a></span><span class="op">(</span><span class="va">data</span><span class="op">$</span><span class="va">mo</span> <span class="op"><a href="../reference/like.html">%like%</a></span> <span class="st">"coli"</span>, <span class="st">"UTI"</span>, <span class="st">"No UTI"</span><span class="op">)</span></span></code></pre></div>
+</div>
+<div class="section level3">
+<h3 id="basic-wisca-antibiogram">Basic WISCA antibiogram<a class="anchor" aria-label="anchor" href="#basic-wisca-antibiogram"></a>
+</h3>
+<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="fu"><a href="../reference/antibiogram.html">wisca</a></span><span class="op">(</span><span class="va">data</span>,</span>
+<span>      antimicrobials <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"AMC"</span>, <span class="st">"CIP"</span>, <span class="st">"GEN"</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
+<table class="table">
+<thead><tr class="header">
+<th align="left">Amoxicillin/clavulanic acid</th>
+<th align="left">Ciprofloxacin</th>
+<th align="left">Gentamicin</th>
+</tr></thead>
+<tbody><tr class="odd">
+<td align="left">73.7% (71.7-75.8%)</td>
+<td align="left">77% (74.3-79.4%)</td>
+<td align="left">72.8% (70.7-74.8%)</td>
+</tr></tbody>
+</table>
+</div>
+<div class="section level3">
+<h3 id="use-combination-regimens">Use combination regimens<a class="anchor" aria-label="anchor" href="#use-combination-regimens"></a>
+</h3>
+<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="fu"><a href="../reference/antibiogram.html">wisca</a></span><span class="op">(</span><span class="va">data</span>,</span>
+<span>      antimicrobials <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"AMC"</span>, <span class="st">"AMC + CIP"</span>, <span class="st">"AMC + GEN"</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
+<table class="table">
+<colgroup>
+<col width="24%">
+<col width="38%">
+<col width="36%">
+</colgroup>
+<thead><tr class="header">
+<th align="left">Amoxicillin/clavulanic acid</th>
+<th align="left">Amoxicillin/clavulanic acid + Ciprofloxacin</th>
+<th align="left">Amoxicillin/clavulanic acid + Gentamicin</th>
+</tr></thead>
+<tbody><tr class="odd">
+<td align="left">73.8% (71.8-75.7%)</td>
+<td align="left">87.5% (85.9-89%)</td>
+<td align="left">89.7% (88.2-91.1%)</td>
+</tr></tbody>
+</table>
+</div>
+<div class="section level3">
+<h3 id="stratify-by-syndrome">Stratify by syndrome<a class="anchor" aria-label="anchor" href="#stratify-by-syndrome"></a>
+</h3>
+<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="fu"><a href="../reference/antibiogram.html">wisca</a></span><span class="op">(</span><span class="va">data</span>,</span>
+<span>      antimicrobials <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"AMC"</span>, <span class="st">"AMC + CIP"</span>, <span class="st">"AMC + GEN"</span><span class="op">)</span>,</span>
+<span>      syndromic_group <span class="op">=</span> <span class="st">"syndrome"</span><span class="op">)</span></span></code></pre></div>
+<table class="table">
+<colgroup>
+<col width="12%">
+<col width="21%">
+<col width="34%">
+<col width="31%">
+</colgroup>
+<thead><tr class="header">
+<th align="left">Syndromic Group</th>
+<th align="left">Amoxicillin/clavulanic acid</th>
+<th align="left">Amoxicillin/clavulanic acid + Ciprofloxacin</th>
+<th align="left">Amoxicillin/clavulanic acid + Gentamicin</th>
+</tr></thead>
+<tbody>
+<tr class="odd">
+<td align="left">No UTI</td>
+<td align="left">70.1% (67.8-72.3%)</td>
+<td align="left">85.2% (83.1-87.2%)</td>
+<td align="left">87.1% (85.3-88.7%)</td>
+</tr>
+<tr class="even">
+<td align="left">UTI</td>
+<td align="left">80.9% (77.7-83.8%)</td>
+<td align="left">88.2% (85.7-90.5%)</td>
+<td align="left">90.9% (88.7-93%)</td>
+</tr>
+</tbody>
+</table>
+<p>The <code>AMR</code> package is available in 28 languages, which can
+all be used for the <code><a href="../reference/antibiogram.html">wisca()</a></code> function too:</p>
+<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="fu"><a href="../reference/antibiogram.html">wisca</a></span><span class="op">(</span><span class="va">data</span>,</span>
+<span>      antimicrobials <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"AMC"</span>, <span class="st">"AMC + CIP"</span>, <span class="st">"AMC + GEN"</span><span class="op">)</span>,</span>
+<span>      syndromic_group <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/grep.html" class="external-link">gsub</a></span><span class="op">(</span><span class="st">"UTI"</span>, <span class="st">"UCI"</span>, <span class="va">data</span><span class="op">$</span><span class="va">syndrome</span><span class="op">)</span>,</span>
+<span>      language <span class="op">=</span> <span class="st">"Spanish"</span><span class="op">)</span></span></code></pre></div>
+<table class="table">
+<colgroup>
+<col width="12%">
+<col width="21%">
+<col width="34%">
+<col width="31%">
+</colgroup>
+<thead><tr class="header">
+<th align="left">Grupo sindrómico</th>
+<th align="left">Amoxicilina/ácido clavulánico</th>
+<th align="left">Amoxicilina/ácido clavulánico + Ciprofloxacina</th>
+<th align="left">Amoxicilina/ácido clavulánico + Gentamicina</th>
+</tr></thead>
+<tbody>
+<tr class="odd">
+<td align="left">No UCI</td>
+<td align="left">70% (67.8-72.4%)</td>
+<td align="left">85.3% (83.3-87.2%)</td>
+<td align="left">87% (85.3-88.8%)</td>
+</tr>
+<tr class="even">
+<td align="left">UCI</td>
+<td align="left">80.9% (77.7-83.9%)</td>
+<td align="left">88.2% (85.5-90.6%)</td>
+<td align="left">90.9% (88.7-93%)</td>
+</tr>
+</tbody>
+</table>
+</div>
+</div>
+<div class="section level2">
+<h2 id="sensible-defaults-which-can-be-customised">Sensible defaults, which can be customised<a class="anchor" aria-label="anchor" href="#sensible-defaults-which-can-be-customised"></a>
+</h2>
+<ul>
+<li>
+<code>simulations = 1000</code>: number of Monte Carlo draws</li>
+<li>
+<code>conf_interval = 0.95</code>: coverage interval width</li>
+<li>
+<code>combine_SI = TRUE</code>: count “I” and “SDD” as
+susceptible</li>
+</ul>
+</div>
+<div class="section level2">
+<h2 id="limitations">Limitations<a class="anchor" aria-label="anchor" href="#limitations"></a>
+</h2>
+<ul>
+<li>It assumes your data are representative</li>
+<li>No adjustment for patient-level covariates, although these could be
+passed onto the <code>syndromic_group</code> argument</li>
+<li>WISCA does not model resistance over time, you might want to use
+<code>tidymodels</code> for that, for which we <a href="https://amr-for-r.org/articles/AMR_with_tidymodels.html">wrote a
+basic introduction</a>
+</li>
+</ul>
+</div>
+<div class="section level2">
+<h2 id="summary">Summary<a class="anchor" aria-label="anchor" href="#summary"></a>
+</h2>
+<p>WISCA enables:</p>
+<ul>
+<li>Empirical regimen comparison,</li>
+<li>Syndrome-specific coverage estimation,</li>
+<li>Fully probabilistic interpretation.</li>
+</ul>
+<p>It is available in the <code>AMR</code> package via either:</p>
+<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="fu"><a href="../reference/antibiogram.html">wisca</a></span><span class="op">(</span><span class="va">...</span><span class="op">)</span></span>
+<span></span>
+<span><span class="fu"><a href="../reference/antibiogram.html">antibiogram</a></span><span class="op">(</span><span class="va">...</span>, wisca <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
+</div>
+<div class="section level2">
+<h2 id="reference">Reference<a class="anchor" aria-label="anchor" href="#reference"></a>
+</h2>
+<p>Bielicki, JA, et al. (2016). <em>Selecting appropriate empirical
+antibiotic regimens for paediatric bloodstream infections: application
+of a Bayesian decision model to local and pooled antimicrobial
+resistance surveillance data.</em> <strong>J Antimicrob
+Chemother</strong>. 71(3):794-802. <a href="https://doi.org/10.1093/jac/dkv397" class="external-link uri">https://doi.org/10.1093/jac/dkv397</a></p>
+</div>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
+    </nav></aside>
+</div>
+
+
+
+    <footer><div class="pkgdown-footer-left">
+  <p><code>AMR</code> (for R). Free and open-source, licenced under the <a target="_blank" href="https://github.com/msberends/AMR/blob/main/LICENSE" class="external-link">GNU General Public License version 2.0 (GPL-2)</a>.<br>Developed at the <a target="_blank" href="https://www.rug.nl" class="external-link">University of Groningen</a> and <a target="_blank" href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a> in The Netherlands.</p>
+</div>
+
+<div class="pkgdown-footer-right">
+  <p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://amr-for-r.org/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://amr-for-r.org/logo_umcg.svg" style="max-width: 150px;"></a></p>
+</div>
+
+    </footer>
+</div>
+
+
+
+
+
+  </body>
+</html>

articles/index.html

@@ -1,5 +1,5 @@
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-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Articles • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Articles"><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Articles • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="96x96" href="../favicon-96x96.png"><link rel="icon" type="”image/svg+xml”" href="../favicon.svg"><link rel="apple-touch-icon" sizes="180x180" href="../apple-touch-icon.png"><link rel="icon" sizes="any" href="../favicon.ico"><link rel="manifest" href="../site.webmanifest"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.10/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.10/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Articles"><meta property="og:image" content="https://amr-for-r.org/logo.svg"><link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/katex@0.16.11/dist/katex.min.css" integrity="sha384-nB0miv6/jRmo5UMMR1wu3Gz6NLsoTkbqJghGIsx//Rlm+ZU03BU6SQNC66uf4l5+" crossorigin="anonymous"><script defer src="https://cdn.jsdelivr.net/npm/katex@0.16.11/dist/katex.min.js" integrity="sha384-7zkQWkzuo3B5mTepMUcHkMB5jZaolc2xDwL6VFqjFALcbeS9Ggm/Yr2r3Dy4lfFg" crossorigin="anonymous"></script><script defer src="https://cdn.jsdelivr.net/npm/katex@0.16.11/dist/contrib/auto-render.min.js" integrity="sha384-43gviWU0YVjaDtb/GhzOouOXtZMP/7XUzwPTstBeZFe/+rCMvRwr4yROQP43s0Xk" crossorigin="anonymous" onload="renderMathInElement(document.body);"></script></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9099</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9033</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -19,13 +19,13 @@
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   <ul class="dropdown-menu" aria-labelledby="dropdown-how-to"><li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
     <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
-    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/AMR_with_tidymodels.html"><span class="fa fa-square-root-variable"></span> Use AMR for Predictive Modelling (tidymodels)</a></li>
     <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
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     <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
-    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../reference/mdro.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
     <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
-    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply EUCAST Rules</a></li>
     <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
     <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
     <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
@@ -33,8 +33,10 @@
 <li class="nav-item"><a class="nav-link" href="../articles/AMR_for_Python.html"><span class="fa fab fa-python"></span> AMR for Python</a></li>
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-      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
-<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
+ <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fa-github"></span> Source Code</a></li>
       </ul></div>
 
 
@@ -51,21 +53,19 @@
 
       <dl><dt><a href="AMR_for_Python.html">AMR for Python</a></dt>
         <dd>
-        </dd><dt><a href="AMR.html">How to conduct AMR data analysis</a></dt>
+        </dd><dt><a href="AMR_with_tidymodels.html">AMR with tidymodels</a></dt>
         <dd>
-        </dd><dt><a href="datasets.html">Data sets for download / own use</a></dt>
+        </dd><dt><a href="AMR.html">Conduct AMR data analysis</a></dt>
         <dd>
-        </dd><dt><a href="EUCAST.html">How to apply EUCAST rules</a></dt>
+        </dd><dt><a href="datasets.html">Download data sets for download / own use</a></dt>
         <dd>
-        </dd><dt><a href="MDR.html">How to determine multi-drug resistance (MDR)</a></dt>
+        </dd><dt><a href="EUCAST.html">Apply EUCAST rules</a></dt>
         <dd>
-        </dd><dt><a href="PCA.html">How to conduct principal component analysis (PCA) for AMR</a></dt>
+        </dd><dt><a href="PCA.html">Conduct principal component analysis (PCA) for AMR</a></dt>
         <dd>
-        </dd><dt><a href="resistance_predict.html">How to predict antimicrobial resistance</a></dt>
+        </dd><dt><a href="WHONET.html">Work with WHONET data</a></dt>
         <dd>
-        </dd><dt><a href="welcome_to_AMR.html">Welcome to the `AMR` package</a></dt>
-        <dd>
-        </dd><dt><a href="WHONET.html">How to work with WHONET data</a></dt>
+        </dd><dt><a href="WISCA.html">Estimating Empirical Coverage with WISCA</a></dt>
         <dd>
       </dd></dl></div>
   </main></div>
@@ -76,7 +76,7 @@
 </div>
 
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-  <p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/assets/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/assets/logo_umcg.svg" style="max-width: 150px;"></a></p>
+  <p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://amr-for-r.org/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://amr-for-r.org/logo_umcg.svg" style="max-width: 150px;"></a></p>
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-
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-
-    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
-
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9099</small>
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-    </button>
-
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-      <ul class="navbar-nav me-auto">
-<li class="active nav-item dropdown">
-  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to">
-<li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
-    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
-    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
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-    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
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-<div class="row">
-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.svg" class="logo" alt=""><h1>How to predict antimicrobial resistance</h1>
-            
-      
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/resistance_predict.Rmd" class="external-link"><code>vignettes/resistance_predict.Rmd</code></a></small>
-      <div class="d-none name"><code>resistance_predict.Rmd</code></div>
-    </div>
-
-    
-    
-<div class="section level2">
-<h2 id="needed-r-packages">Needed R packages<a class="anchor" aria-label="anchor" href="#needed-r-packages"></a>
-</h2>
-<p>As with many uses in R, we need some additional packages for AMR data
-analysis. Our package works closely together with the <a href="https://www.tidyverse.org" class="external-link">tidyverse packages</a> <a href="https://dplyr.tidyverse.org/" class="external-link"><code>dplyr</code></a> and <a href="https://ggplot2.tidyverse.org" class="external-link"><code>ggplot2</code></a>. The
-tidyverse tremendously improves the way we conduct data science - it
-allows for a very natural way of writing syntaxes and creating beautiful
-plots in R.</p>
-<p>Our <code>AMR</code> package depends on these packages and even
-extends their use and functions.</p>
-<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span>
-<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span></span>
-<span></span>
-<span><span class="co"># (if not yet installed, install with:)</span></span>
-<span><span class="co"># install.packages(c("tidyverse", "AMR"))</span></span></code></pre></div>
-</div>
-<div class="section level2">
-<h2 id="prediction-analysis">Prediction analysis<a class="anchor" aria-label="anchor" href="#prediction-analysis"></a>
-</h2>
-<p>Our package contains a function <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>,
-which takes the same input as functions for <a href="./AMR.html">other
-AMR data analysis</a>. Based on a date column, it calculates cases per
-year and uses a regression model to predict antimicrobial
-resistance.</p>
-<p>It is basically as easy as:</p>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># resistance prediction of piperacillin/tazobactam (TZP):</span></span>
-<span><span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span><span class="op">(</span>tbl <span class="op">=</span> <span class="va">example_isolates</span>, col_date <span class="op">=</span> <span class="st">"date"</span>, col_ab <span class="op">=</span> <span class="st">"TZP"</span>, model <span class="op">=</span> <span class="st">"binomial"</span><span class="op">)</span></span>
-<span></span>
-<span><span class="co"># or:</span></span>
-<span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span><span class="op">(</span></span>
-<span>    col_ab <span class="op">=</span> <span class="st">"TZP"</span>,</span>
-<span>    model <span class="op">=</span> <span class="st">"binomial"</span></span>
-<span>  <span class="op">)</span></span>
-<span></span>
-<span><span class="co"># to bind it to object 'predict_TZP' for example:</span></span>
-<span><span class="va">predict_TZP</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span><span class="op">(</span></span>
-<span>    col_ab <span class="op">=</span> <span class="st">"TZP"</span>,</span>
-<span>    model <span class="op">=</span> <span class="st">"binomial"</span></span>
-<span>  <span class="op">)</span></span></code></pre></div>
-<p>The function will look for a date column itself if
-<code>col_date</code> is not set.</p>
-<p>When running any of these commands, a summary of the regression model
-will be printed unless using
-<code>resistance_predict(..., info = FALSE)</code>.</p>
-<p>This text is only a printed summary - the actual result (output) of
-the function is a <code>data.frame</code> containing for each year: the
-number of observations, the actual observed resistance, the estimated
-resistance and the standard error below and above the estimation:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">predict_TZP</span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 33 × 7</span></span></span>
-<span><span class="co">#&gt;     year  value se_min se_max observations observed estimated</span></span>
-<span><span class="co">#&gt;  <span style="color: #BCBCBC;">*</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>        <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 1</span>  <span style="text-decoration: underline;">2</span>002 0.2        <span style="color: #BB0000;">NA</span>     <span style="color: #BB0000;">NA</span>           15   0.2       0.056<span style="text-decoration: underline;">2</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 2</span>  <span style="text-decoration: underline;">2</span>003 0.062<span style="text-decoration: underline;">5</span>     <span style="color: #BB0000;">NA</span>     <span style="color: #BB0000;">NA</span>           32   0.062<span style="text-decoration: underline;">5</span>    0.061<span style="text-decoration: underline;">6</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 3</span>  <span style="text-decoration: underline;">2</span>004 0.085<span style="text-decoration: underline;">4</span>     <span style="color: #BB0000;">NA</span>     <span style="color: #BB0000;">NA</span>           82   0.085<span style="text-decoration: underline;">4</span>    0.067<span style="text-decoration: underline;">6</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 4</span>  <span style="text-decoration: underline;">2</span>005 0.05       <span style="color: #BB0000;">NA</span>     <span style="color: #BB0000;">NA</span>           60   0.05      0.074<span style="text-decoration: underline;">1</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 5</span>  <span style="text-decoration: underline;">2</span>006 0.050<span style="text-decoration: underline;">8</span>     <span style="color: #BB0000;">NA</span>     <span style="color: #BB0000;">NA</span>           59   0.050<span style="text-decoration: underline;">8</span>    0.081<span style="text-decoration: underline;">2</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 6</span>  <span style="text-decoration: underline;">2</span>007 0.121      <span style="color: #BB0000;">NA</span>     <span style="color: #BB0000;">NA</span>           66   0.121     0.088<span style="text-decoration: underline;">9</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 7</span>  <span style="text-decoration: underline;">2</span>008 0.041<span style="text-decoration: underline;">7</span>     <span style="color: #BB0000;">NA</span>     <span style="color: #BB0000;">NA</span>           72   0.041<span style="text-decoration: underline;">7</span>    0.097<span style="text-decoration: underline;">2</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span>  <span style="text-decoration: underline;">2</span>009 0.016<span style="text-decoration: underline;">4</span>     <span style="color: #BB0000;">NA</span>     <span style="color: #BB0000;">NA</span>           61   0.016<span style="text-decoration: underline;">4</span>    0.106 </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span>  <span style="text-decoration: underline;">2</span>010 0.056<span style="text-decoration: underline;">6</span>     <span style="color: #BB0000;">NA</span>     <span style="color: #BB0000;">NA</span>           53   0.056<span style="text-decoration: underline;">6</span>    0.116 </span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span>  <span style="text-decoration: underline;">2</span>011 0.183      <span style="color: #BB0000;">NA</span>     <span style="color: #BB0000;">NA</span>           93   0.183     0.127 </span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 23 more rows</span></span></span></code></pre></div>
-<p>The function <code>plot</code> is available in base R, and can be
-extended by other packages to depend the output based on the type of
-input. We extended its function to cope with resistance predictions:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/plot.html">plot</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span></span></code></pre></div>
-<p><img src="resistance_predict_files/figure-html/unnamed-chunk-4-1.png" width="720"></p>
-<p>This is the fastest way to plot the result. It automatically adds the
-right axes, error bars, titles, number of available observations and
-type of model.</p>
-<p>We also support the <code>ggplot2</code> package with our custom
-function <code><a href="../reference/resistance_predict.html">ggplot_sir_predict()</a></code> to create more appealing
-plots:</p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/resistance_predict.html">ggplot_sir_predict</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span></span></code></pre></div>
-<p><img src="resistance_predict_files/figure-html/unnamed-chunk-5-1.png" width="720"></p>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
-<span><span class="co"># choose for error bars instead of a ribbon</span></span>
-<span><span class="fu"><a href="../reference/resistance_predict.html">ggplot_sir_predict</a></span><span class="op">(</span><span class="va">predict_TZP</span>, ribbon <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div>
-<p><img src="resistance_predict_files/figure-html/unnamed-chunk-5-2.png" width="720"></p>
-<div class="section level3">
-<h3 id="choosing-the-right-model">Choosing the right model<a class="anchor" aria-label="anchor" href="#choosing-the-right-model"></a>
-</h3>
-<p>Resistance is not easily predicted; if we look at vancomycin
-resistance in Gram-positive bacteria, the spread (i.e. standard error)
-is enormous:</p>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">mo</span>, language <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Gram-positive"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span><span class="op">(</span>col_ab <span class="op">=</span> <span class="st">"VAN"</span>, year_min <span class="op">=</span> <span class="fl">2010</span>, info <span class="op">=</span> <span class="cn">FALSE</span>, model <span class="op">=</span> <span class="st">"binomial"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/resistance_predict.html">ggplot_sir_predict</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<p><img src="resistance_predict_files/figure-html/unnamed-chunk-6-1.png" width="720"></p>
-<p>Vancomycin resistance could be 100% in ten years, but might remain
-very low.</p>
-<p>You can define the model with the <code>model</code> parameter. The
-model chosen above is a generalised linear regression model using a
-binomial distribution, assuming that a period of zero resistance was
-followed by a period of increasing resistance leading slowly to more and
-more resistance.</p>
-<p>Valid values are:</p>
-<table class="table">
-<colgroup>
-<col width="32%">
-<col width="25%">
-<col width="42%">
-</colgroup>
-<thead><tr class="header">
-<th>Input values</th>
-<th>Function used by R</th>
-<th>Type of model</th>
-</tr></thead>
-<tbody>
-<tr class="odd">
-<td>
-<code>"binomial"</code> or <code>"binom"</code> or
-<code>"logit"</code>
-</td>
-<td><code>glm(..., family = binomial)</code></td>
-<td>Generalised linear model with binomial distribution</td>
-</tr>
-<tr class="even">
-<td>
-<code>"loglin"</code> or <code>"poisson"</code>
-</td>
-<td><code>glm(..., family = poisson)</code></td>
-<td>Generalised linear model with poisson distribution</td>
-</tr>
-<tr class="odd">
-<td>
-<code>"lin"</code> or <code>"linear"</code>
-</td>
-<td><code><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm()</a></code></td>
-<td>Linear model</td>
-</tr>
-</tbody>
-</table>
-<p>For the vancomycin resistance in Gram-positive bacteria, a linear
-model might be more appropriate:</p>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">mo</span>, language <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Gram-positive"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span><span class="op">(</span>col_ab <span class="op">=</span> <span class="st">"VAN"</span>, year_min <span class="op">=</span> <span class="fl">2010</span>, info <span class="op">=</span> <span class="cn">FALSE</span>, model <span class="op">=</span> <span class="st">"linear"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="../reference/resistance_predict.html">ggplot_sir_predict</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
-<p><img src="resistance_predict_files/figure-html/unnamed-chunk-7-1.png" width="720"></p>
-<p>The model itself is also available from the object, as an
-<code>attribute</code>:</p>
-<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="va">model</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/attributes.html" class="external-link">attributes</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span><span class="op">$</span><span class="va">model</span></span>
-<span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">$</span><span class="va">family</span></span>
-<span><span class="co">#&gt; </span></span>
-<span><span class="co">#&gt; Family: binomial </span></span>
-<span><span class="co">#&gt; Link function: logit</span></span>
-<span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">$</span><span class="va">coefficients</span></span>
-<span><span class="co">#&gt;                  Estimate  Std. Error   z value     Pr(&gt;|z|)</span></span>
-<span><span class="co">#&gt; (Intercept) -200.67944891 46.17315349 -4.346237 1.384932e-05</span></span>
-<span><span class="co">#&gt; year           0.09883005  0.02295317  4.305725 1.664395e-05</span></span></code></pre></div>
-</div>
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-<script src="../extra.js"></script><meta property="og:title" content="Welcome to the `AMR` package">
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-    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
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-    <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9099</small>
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-  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to">
-<li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
-    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
-    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
-    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
-    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
-    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
-    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
-    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
-    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
-    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
-    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
-    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
-  </ul>
-</li>
-<li class="nav-item"><a class="nav-link" href="../articles/AMR_for_Python.html"><span class="fa fab fa-python"></span> AMR for Python</a></li>
-<li class="nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
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-<div class="row">
-  <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.svg" class="logo" alt=""><h1>Welcome to the `AMR` package</h1>
-            
-      
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/welcome_to_AMR.Rmd" class="external-link"><code>vignettes/welcome_to_AMR.Rmd</code></a></small>
-      <div class="d-none name"><code>welcome_to_AMR.Rmd</code></div>
-    </div>
-
-    
-    
-<p>Note: to keep the package size as small as possible, we only include
-this vignette on CRAN. You can read more vignettes on our website about
-how to conduct AMR data analysis, determine MDROs, find explanation of
-EUCAST and CLSI breakpoints, and much more: <a href="https://msberends.github.io/AMR/articles/" class="uri">https://msberends.github.io/AMR/articles/</a>.</p>
-<hr>
-<p>The <code>AMR</code> package is a <a href="https://msberends.github.io/AMR/#copyright">free and
-open-source</a> R package with <a href="https://en.wikipedia.org/wiki/Dependency_hell" class="external-link">zero
-dependencies</a> to simplify the analysis and prediction of
-Antimicrobial Resistance (AMR) and to work with microbial and
-antimicrobial data and properties, by using evidence-based methods.
-<strong>Our aim is to provide a standard</strong> for clean and
-reproducible AMR data analysis, that can therefore empower
-epidemiological analyses to continuously enable surveillance and
-treatment evaluation in any setting. <a href="https://msberends.github.io/AMR/authors.html">Many different
-researchers</a> from around the globe are continually helping us to make
-this a successful and durable project!</p>
-<p>This work was published in the Journal of Statistical Software
-(Volume 104(3); <a href="https://doi.org/10.18637/jss.v104.i03" class="external-link">DOI
-10.18637/jss.v104.i03</a>) and formed the basis of two PhD theses (<a href="https://doi.org/10.33612/diss.177417131" class="external-link">DOI
-10.33612/diss.177417131</a> and <a href="https://doi.org/10.33612/diss.192486375" class="external-link">DOI
-10.33612/diss.192486375</a>).</p>
-<p>After installing this package, R knows ~79 000 distinct microbial
-species and all ~600 antibiotic, antimycotic and antiviral drugs by name
-and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED
-CT), and knows all about valid SIR and MIC values. The integral
-breakpoint guidelines from CLSI and EUCAST are included from the last 10
-years. It supports and can read any data format, including WHONET
-data.</p>
-<p>With the help of contributors from all corners of the world, the
-<code>AMR</code> package is available in English, Czech, Chinese,
-Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese,
-Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish,
-Turkish, and Ukrainian. Antimicrobial drug (group) names and colloquial
-microorganism names are provided in these languages.</p>
-<p>This package is fully independent of any other R package and works on
-Windows, macOS and Linux with all versions of R since R-3.0 (April
-2013). <strong>It was designed to work in any setting, including those
-with very limited resources</strong>. Since its first public release in
-early 2018, this package has been downloaded from more than 175
-countries.</p>
-<p>This package can be used for:</p>
-<ul>
-<li>Reference for the taxonomy of microorganisms, since the package
-contains all microbial (sub)species from the List of Prokaryotic names
-with Standing in Nomenclature (LPSN) and the Global Biodiversity
-Information Facility (GBIF)</li>
-<li>Interpreting raw MIC and disk diffusion values, based on the latest
-CLSI or EUCAST guidelines</li>
-<li>Retrieving antimicrobial drug names, doses and forms of
-administration from clinical health care records</li>
-<li>Determining first isolates to be used for AMR data analysis</li>
-<li>Calculating antimicrobial resistance</li>
-<li>Determining multi-drug resistance (MDR) / multi-drug resistant
-organisms (MDRO)</li>
-<li>Calculating (empirical) susceptibility of both mono therapy and
-combination therapies</li>
-<li>Predicting future antimicrobial resistance using regression
-models</li>
-<li>Getting properties for any microorganism (like Gram stain, species,
-genus or family)</li>
-<li>Getting properties for any antibiotic (like name, code of
-EARS-Net/ATC/LOINC/PubChem, defined daily dose or trade name)</li>
-<li>Plotting antimicrobial resistance</li>
-<li>Applying EUCAST expert rules</li>
-<li>Getting SNOMED codes of a microorganism, or getting properties of a
-microorganism based on a SNOMED code</li>
-<li>Getting LOINC codes of an antibiotic, or getting properties of an
-antibiotic based on a LOINC code</li>
-<li>Machine reading the EUCAST and CLSI guidelines from 2011-2020 to
-translate MIC values and disk diffusion diameters to SIR</li>
-<li>Principal component analysis for AMR</li>
-</ul>
-<p>All reference data sets (about microorganisms, antibiotics, SIR
-interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are
-publicly and freely available. We continually export our data sets to
-formats for use in R, SPSS, Stata and Excel. We also supply flat files
-that are machine-readable and suitable for input in any software
-program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all
-download links on our website</a>, which is automatically updated with
-every code change.</p>
-<p>This R package was created for both routine data analysis and
-academic research at the Faculty of Medical Sciences of the <a href="https://www.rug.nl" class="external-link">University of Groningen</a>, in collaboration
-with non-profit organisations <a href="https://www.certe.nl" class="external-link">Certe
-Medical Diagnostics and Advice Foundation</a> and <a href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a>, and
-is being <a href="https://msberends.github.io/AMR/news/">actively and
-durably maintained</a> by two public healthcare organisations in the
-Netherlands.</p>
-<hr>
-<p><small> This AMR package for R is free, open-source software and
-licensed under the <a href="https://msberends.github.io/AMR/LICENSE-text.html">GNU General
-Public License v2.0 (GPL-2)</a>. These requirements are consequently
-legally binding: modifications must be released under the same license
-when distributing the package, changes made to the code must be
-documented, source code must be made available when the package is
-distributed, and a copy of the license and copyright notice must be
-included with the package. </small></p>
-  </main>
-</div>
-
-
-
-    <footer><div class="pkgdown-footer-left">
-  <p><code>AMR</code> (for R). Free and open-source, licenced under the <a target="_blank" href="https://github.com/msberends/AMR/blob/main/LICENSE" class="external-link">GNU General Public License version 2.0 (GPL-2)</a>.<br>Developed at the <a target="_blank" href="https://www.rug.nl" class="external-link">University of Groningen</a> and <a target="_blank" href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a> in The Netherlands.</p>
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authors.html

@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Authors and Citation • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="deps/headroom-0.11.0/headroom.min.js"></script><script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="deps/search-1.0.0/fuse.min.js"></script><script src="deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="pkgdown.js"></script><link href="extra.css" rel="stylesheet"><script src="extra.js"></script><meta property="og:title" content="Authors and Citation"><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Authors and Citation • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="96x96" href="favicon-96x96.png"><link rel="icon" type="”image/svg+xml”" href="favicon.svg"><link rel="apple-touch-icon" sizes="180x180" href="apple-touch-icon.png"><link rel="icon" sizes="any" href="favicon.ico"><link rel="manifest" href="site.webmanifest"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="deps/Lato-0.4.10/font.css" rel="stylesheet"><link href="deps/Fira_Code-0.4.10/font.css" rel="stylesheet"><link href="deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="deps/headroom-0.11.0/headroom.min.js"></script><script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="deps/search-1.0.0/fuse.min.js"></script><script src="deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="pkgdown.js"></script><link href="extra.css" rel="stylesheet"><script src="extra.js"></script><meta property="og:title" content="Authors and Citation"><meta property="og:image" content="https://amr-for-r.org/logo.svg"><link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/katex@0.16.11/dist/katex.min.css" integrity="sha384-nB0miv6/jRmo5UMMR1wu3Gz6NLsoTkbqJghGIsx//Rlm+ZU03BU6SQNC66uf4l5+" crossorigin="anonymous"><script defer src="https://cdn.jsdelivr.net/npm/katex@0.16.11/dist/katex.min.js" integrity="sha384-7zkQWkzuo3B5mTepMUcHkMB5jZaolc2xDwL6VFqjFALcbeS9Ggm/Yr2r3Dy4lfFg" crossorigin="anonymous"></script><script defer src="https://cdn.jsdelivr.net/npm/katex@0.16.11/dist/contrib/auto-render.min.js" integrity="sha384-43gviWU0YVjaDtb/GhzOouOXtZMP/7XUzwPTstBeZFe/+rCMvRwr4yROQP43s0Xk" crossorigin="anonymous" onload="renderMathInElement(document.body);"></script></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9099</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9033</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -19,13 +19,13 @@
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   <ul class="dropdown-menu" aria-labelledby="dropdown-how-to"><li><a class="dropdown-item" href="articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
     <li><a class="dropdown-item" href="reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
-    <li><a class="dropdown-item" href="articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="articles/AMR_with_tidymodels.html"><span class="fa fa-square-root-variable"></span> Use AMR for Predictive Modelling (tidymodels)</a></li>
     <li><a class="dropdown-item" href="articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
     <li><a class="dropdown-item" href="reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
     <li><a class="dropdown-item" href="articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
-    <li><a class="dropdown-item" href="articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="reference/mdro.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
     <li><a class="dropdown-item" href="articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
-    <li><a class="dropdown-item" href="articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply EUCAST Rules</a></li>
     <li><a class="dropdown-item" href="reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
     <li><a class="dropdown-item" href="reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
     <li><a class="dropdown-item" href="reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
@@ -33,8 +33,10 @@
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 <li class="nav-item"><a class="nav-link" href="reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
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-      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
-<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
+ <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
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       </ul></div>
 
 
@@ -61,27 +63,39 @@
           </p>
         </li>
         <li>
-          <p><strong>Casper J. Albers</strong>. Thesis advisor. <a href="https://orcid.org/0000-0002-9213-6743" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          <p><strong>Aislinn Cook</strong>. Contributor. <a href="https://orcid.org/0000-0002-9189-7815" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
           </p>
         </li>
         <li>
-          <p><strong>Larisse Bolton</strong>. Contributor. <a href="https://orcid.org/0000-0001-7879-2173" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          <p><strong>Andrew P. Norgan</strong>. Contributor. <a href="https://orcid.org/0000-0002-2955-2066" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
           </p>
         </li>
         <li>
-          <p><strong>Peter Dutey-Magni</strong>. Contributor. <a href="https://orcid.org/0000-0002-8942-9836" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          <p><strong>Anita Williams</strong>. Contributor. <a href="https://orcid.org/0000-0002-5295-8451" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
           </p>
         </li>
         <li>
-          <p><strong>Judith M. Fonville</strong>. Contributor.
+          <p><strong>Annick Lenglet</strong>. Contributor. <a href="https://orcid.org/0000-0003-2013-8405" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
           </p>
         </li>
         <li>
-          <p><strong>Alex W. Friedrich</strong>. Thesis advisor. <a href="https://orcid.org/0000-0003-4881-038X" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          <p><strong>Anthony Underwood</strong>. Contributor. <a href="https://orcid.org/0000-0002-8547-4277" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
           </p>
         </li>
         <li>
-          <p><strong>Corinna Glasner</strong>. Thesis advisor. <a href="https://orcid.org/0000-0003-1241-1328" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          <p><strong>Anton Mymrikov</strong>. Contributor.
+          </p>
+        </li>
+        <li>
+          <p><strong>Bart C. Meijer</strong>. Contributor.
+          </p>
+        </li>
+        <li>
+          <p><strong>Christian F. Luz</strong>. Contributor. <a href="https://orcid.org/0000-0001-5809-5995" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          </p>
+        </li>
+        <li>
+          <p><strong>Dmytro Mykhailenko</strong>. Contributor.
           </p>
         </li>
         <li>
@@ -93,51 +107,7 @@
           </p>
         </li>
         <li>
-          <p><strong>Annick Lenglet</strong>. Contributor. <a href="https://orcid.org/0000-0003-2013-8405" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
-          </p>
-        </li>
-        <li>
-          <p><strong>Christian F. Luz</strong>. Contributor. <a href="https://orcid.org/0000-0001-5809-5995" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
-          </p>
-        </li>
-        <li>
-          <p><strong>Bart C. Meijer</strong>. Contributor.
-          </p>
-        </li>
-        <li>
-          <p><strong>Dmytro Mykhailenko</strong>. Contributor.
-          </p>
-        </li>
-        <li>
-          <p><strong>Anton Mymrikov</strong>. Contributor.
-          </p>
-        </li>
-        <li>
-          <p><strong>Andrew P. Norgan</strong>. Contributor. <a href="https://orcid.org/0000-0002-2955-2066" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
-          </p>
-        </li>
-        <li>
-          <p><strong>Sofia Ny</strong>. Contributor. <a href="https://orcid.org/0000-0002-2017-1363" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
-          </p>
-        </li>
-        <li>
-          <p><strong>Matthew Saab</strong>. Contributor.
-          </p>
-        </li>
-        <li>
-          <p><strong>Jonas Salm</strong>. Contributor.
-          </p>
-        </li>
-        <li>
-          <p><strong>Javier Sanchez</strong>. Contributor. <a href="https://orcid.org/0000-0003-2605-8094" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
-          </p>
-        </li>
-        <li>
-          <p><strong>Rogier P. Schade</strong>. Contributor.
-          </p>
-        </li>
-        <li>
-          <p><strong>Bhanu N. M. Sinha</strong>. Thesis advisor. <a href="https://orcid.org/0000-0003-1634-0010" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          <p><strong>Jane Hawkey</strong>. Contributor. <a href="https://orcid.org/0000-0001-9661-5293" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
           </p>
         </li>
         <li>
@@ -145,11 +115,59 @@
           </p>
         </li>
         <li>
-          <p><strong>Anthony Underwood</strong>. Contributor. <a href="https://orcid.org/0000-0002-8547-4277" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          <p><strong>Javier Sanchez</strong>. Contributor. <a href="https://orcid.org/0000-0003-2605-8094" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
           </p>
         </li>
         <li>
-          <p><strong>Anita Williams</strong>. Contributor. <a href="https://orcid.org/0000-0002-5295-8451" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          <p><strong>Jonas Salm</strong>. Contributor.
+          </p>
+        </li>
+        <li>
+          <p><strong>Judith M. Fonville</strong>. Contributor.
+          </p>
+        </li>
+        <li>
+          <p><strong>Kathryn Holt</strong>. Contributor. <a href="https://orcid.org/0000-0003-3949-2471" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          </p>
+        </li>
+        <li>
+          <p><strong>Larisse Bolton</strong>. Contributor. <a href="https://orcid.org/0000-0001-7879-2173" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          </p>
+        </li>
+        <li>
+          <p><strong>Matthew Saab</strong>. Contributor.
+          </p>
+        </li>
+        <li>
+          <p><strong>Natacha Couto</strong>. Contributor. <a href="https://orcid.org/0000-0002-9152-5464" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          </p>
+        </li>
+        <li>
+          <p><strong>Peter Dutey-Magni</strong>. Contributor. <a href="https://orcid.org/0000-0002-8942-9836" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          </p>
+        </li>
+        <li>
+          <p><strong>Rogier P. Schade</strong>. Contributor.
+          </p>
+        </li>
+        <li>
+          <p><strong>Sofia Ny</strong>. Contributor. <a href="https://orcid.org/0000-0002-2017-1363" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          </p>
+        </li>
+        <li>
+          <p><strong>Alex W. Friedrich</strong>. Thesis advisor. <a href="https://orcid.org/0000-0003-4881-038X" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          </p>
+        </li>
+        <li>
+          <p><strong>Bhanu N. M. Sinha</strong>. Thesis advisor. <a href="https://orcid.org/0000-0003-1634-0010" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          </p>
+        </li>
+        <li>
+          <p><strong>Casper J. Albers</strong>. Thesis advisor. <a href="https://orcid.org/0000-0002-9213-6743" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          </p>
+        </li>
+        <li>
+          <p><strong>Corinna Glasner</strong>. Thesis advisor. <a href="https://orcid.org/0000-0003-1241-1328" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
           </p>
         </li>
       </ul></div>
@@ -184,7 +202,7 @@
 </div>
 
 <div class="pkgdown-footer-right">
-  <p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/assets/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/assets/logo_umcg.svg" style="max-width: 150px;"></a></p>
+  <p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://amr-for-r.org/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://amr-for-r.org/logo_umcg.svg" style="max-width: 150px;"></a></p>
 </div>
 
     </footer></div>

deps/Fira_Code-0.4.10/font.css

@@ -34,6 +34,15 @@
   src: url(uU9eCBsR6Z2vfE9aq3bL0fxyUs4tcw4W_D1sJVP7Nv7g.woff2) format('woff2');
   unicode-range: U+0370-0377, U+037A-037F, U+0384-038A, U+038C, U+038E-03A1, U+03A3-03FF;
 }
+/* symbols2 */
+@font-face {
+  font-family: 'Fira Code';
+  font-style: normal;
+  font-weight: 400;
+  font-display: swap;
+  src: url(uU9eCBsR6Z2vfE9aq3bL0fxyUs4tcw4W_D1sJeraE8PZqw.woff2) format('woff2');
+  unicode-range: U+2000-2001, U+2004-2008, U+200A, U+23B8-23BD, U+2500-259F;
+}
 /* latin-ext */
 @font-face {
   font-family: 'Fira Code';

deps/bootstrap-5.3.1/font.css

@@ -5,7 +5,7 @@
   font-weight: 400;
   font-display: swap;
   src: url(fonts/S6u8w4BMUTPHjxsAUi-qJCY.woff2) format('woff2');
-  unicode-range: U+0100-02AF, U+0304, U+0308, U+0329, U+1E00-1E9F, U+1EF2-1EFF, U+2020, U+20A0-20AB, U+20AD-20C0, U+2113, U+2C60-2C7F, U+A720-A7FF;
+  unicode-range: U+0100-02BA, U+02BD-02C5, U+02C7-02CC, U+02CE-02D7, U+02DD-02FF, U+0304, U+0308, U+0329, U+1D00-1DBF, U+1E00-1E9F, U+1EF2-1EFF, U+2020, U+20A0-20AB, U+20AD-20C0, U+2113, U+2C60-2C7F, U+A720-A7FF;
 }
 /* latin */
 @font-face {
@@ -14,7 +14,7 @@
   font-weight: 400;
   font-display: swap;
   src: url(fonts/S6u8w4BMUTPHjxsAXC-q.woff2) format('woff2');
-  unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+2074, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD;
+  unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD;
 }
 /* latin-ext */
 @font-face {
@@ -23,7 +23,7 @@
   font-weight: 400;
   font-display: swap;
   src: url(fonts/S6uyw4BMUTPHjxAwXjeu.woff2) format('woff2');
-  unicode-range: U+0100-02AF, U+0304, U+0308, U+0329, U+1E00-1E9F, U+1EF2-1EFF, U+2020, U+20A0-20AB, U+20AD-20C0, U+2113, U+2C60-2C7F, U+A720-A7FF;
+  unicode-range: U+0100-02BA, U+02BD-02C5, U+02C7-02CC, U+02CE-02D7, U+02DD-02FF, U+0304, U+0308, U+0329, U+1D00-1DBF, U+1E00-1E9F, U+1EF2-1EFF, U+2020, U+20A0-20AB, U+20AD-20C0, U+2113, U+2C60-2C7F, U+A720-A7FF;
 }
 /* latin */
 @font-face {
@@ -32,7 +32,7 @@
   font-weight: 400;
   font-display: swap;
   src: url(fonts/S6uyw4BMUTPHjx4wXg.woff2) format('woff2');
-  unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+2074, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD;
+  unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD;
 }
 /* latin-ext */
 @font-face {
@@ -41,7 +41,7 @@
   font-weight: 700;
   font-display: swap;
   src: url(fonts/S6u9w4BMUTPHh6UVSwaPGR_p.woff2) format('woff2');
-  unicode-range: U+0100-02AF, U+0304, U+0308, U+0329, U+1E00-1E9F, U+1EF2-1EFF, U+2020, U+20A0-20AB, U+20AD-20C0, U+2113, U+2C60-2C7F, U+A720-A7FF;
+  unicode-range: U+0100-02BA, U+02BD-02C5, U+02C7-02CC, U+02CE-02D7, U+02DD-02FF, U+0304, U+0308, U+0329, U+1D00-1DBF, U+1E00-1E9F, U+1EF2-1EFF, U+2020, U+20A0-20AB, U+20AD-20C0, U+2113, U+2C60-2C7F, U+A720-A7FF;
 }
 /* latin */
 @font-face {
@@ -50,5 +50,5 @@
   font-weight: 700;
   font-display: swap;
   src: url(fonts/S6u9w4BMUTPHh6UVSwiPGQ.woff2) format('woff2');
-  unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+2074, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD;
+  unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD;
 }

deps/data-deps.txt

@@ -2,10 +2,10 @@
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no" />
 <link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet" />
 <script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script>
-<link href="deps/Lato-0.4.9/font.css" rel="stylesheet" />
-<link href="deps/Fira_Code-0.4.9/font.css" rel="stylesheet" />
-<link href="deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet" />
-<link href="deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet" />
+<link href="deps/Lato-0.4.10/font.css" rel="stylesheet" />
+<link href="deps/Fira_Code-0.4.10/font.css" rel="stylesheet" />
+<link href="deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet" />
+<link href="deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet" />
 <script src="deps/headroom-0.11.0/headroom.min.js"></script>
 <script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script>
 <script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script>