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404.html
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<a class="navbar-brand me-2" href="https://msberends.github.io/AMR/index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9134</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9135</small>
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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="">2.1.1.9134</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9135</small>
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articles/AMR.html
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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="">2.1.1.9134</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9135</small>
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@ -90,7 +90,7 @@
website update since they are based on randomly created values and the
page was written in <a href="https://rmarkdown.rstudio.com/" class="external-link">R
Markdown</a>. However, the methodology remains unchanged. This page was
generated on 27 January 2025.</p>
generated on 28 January 2025.</p>
<div class="section level2">
<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
</h2>
@ -146,21 +146,21 @@ make the structure of your data generally look like this:</p>
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2025-01-27</td>
<td align="center">2025-01-28</td>
<td align="center">abcd</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
<tr class="even">
<td align="center">2025-01-27</td>
<td align="center">2025-01-28</td>
<td align="center">abcd</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">R</td>
</tr>
<tr class="odd">
<td align="center">2025-01-27</td>
<td align="center">2025-01-28</td>
<td align="center">efgh</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>

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articles/AMR_for_Python.html
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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="">2.1.1.9134</small>
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articles/AMR_with_tidymodels.html
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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="">2.1.1.9134</small>
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@ -142,7 +142,7 @@ package.</p>
<span><span class="co">#&gt; <span style="color: #BB0000;">✖</span> <span style="color: #0000BB;">dplyr</span>::<span style="color: #00BB00;">filter()</span> masks <span style="color: #0000BB;">stats</span>::filter()</span></span>
<span><span class="co">#&gt; <span style="color: #BB0000;">✖</span> <span style="color: #0000BB;">dplyr</span>::<span style="color: #00BB00;">lag()</span> masks <span style="color: #0000BB;">stats</span>::lag()</span></span>
<span><span class="co">#&gt; <span style="color: #BB0000;">✖</span> <span style="color: #0000BB;">recipes</span>::<span style="color: #00BB00;">step()</span> masks <span style="color: #0000BB;">stats</span>::step()</span></span>
<span><span class="co">#&gt; <span style="color: #0000BB;">•</span> Use <span style="color: #00BB00;">tidymodels_prefer()</span> to resolve common conflicts.</span></span>
<span><span class="co">#&gt; <span style="color: #0000BB;">•</span> Dig deeper into tidy modeling with R at <span style="color: #00BB00;">https://www.tmwr.org</span></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"># For AMR data analysis</span></span>
<span></span>
<span><span class="co"># Load the example_isolates dataset</span></span>

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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="">2.1.1.9134</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9135</small>
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articles/MDR.html
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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="">2.1.1.9134</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9135</small>
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articles/PCA.html
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@ -31,7 +31,7 @@
<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="">2.1.1.9134</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9135</small>
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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="">2.1.1.9134</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9135</small>
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4
articles/datasets.html
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@ -31,7 +31,7 @@
<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="">2.1.1.9134</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9135</small>
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@ -79,7 +79,7 @@
<main id="main" class="col-md-9"><div class="page-header">
<img src="../logo.svg" class="logo" alt=""><h1>Data sets for download / own use</h1>
<h4 data-toc-skip class="date">27 January 2025</h4>
<h4 data-toc-skip class="date">28 January 2025</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/datasets.Rmd" class="external-link"><code>vignettes/datasets.Rmd</code></a></small>
<div class="d-none name"><code>datasets.Rmd</code></div>

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articles/index.html
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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="">2.1.1.9134</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9135</small>
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articles/resistance_predict.html
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@ -31,7 +31,7 @@
<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="">2.1.1.9134</small>
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2
articles/welcome_to_AMR.html
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@ -31,7 +31,7 @@
<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="">2.1.1.9134</small>
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2
authors.html
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@ -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="">2.1.1.9134</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9135</small>
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2
index.html
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@ -34,7 +34,7 @@
<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="">2.1.1.9134</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9135</small>
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news/index.html
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@ -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="">2.1.1.9134</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9135</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">
@ -48,18 +48,18 @@
</div>
<div class="section level2">
<h2 class="pkg-version" data-toc-text="2.1.1.9134" id="amr-2119134">AMR 2.1.1.9134<a class="anchor" aria-label="anchor" href="#amr-2119134"></a></h2>
<h2 class="pkg-version" data-toc-text="2.1.1.9135" id="amr-2119135">AMR 2.1.1.9135<a class="anchor" aria-label="anchor" href="#amr-2119135"></a></h2>
<p><em>(this beta version will eventually become v3.0. We’re happy to reach a new major milestone soon, which will be all about the new One Health support! Install this beta using <a href="https://msberends.github.io/AMR/#latest-development-version">the instructions here</a>.)</em></p>
<div class="section level5">
<h5 id="a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9134">A New Milestone: AMR v3.0 with One Health Support (= Human + Veterinary + Environmental)<a class="anchor" aria-label="anchor" href="#a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9134"></a></h5>
<h5 id="a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9135">A New Milestone: AMR v3.0 with One Health Support (= Human + Veterinary + Environmental)<a class="anchor" aria-label="anchor" href="#a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9135"></a></h5>
<p>This package now supports not only tools for AMR data analysis in clinical settings, but also for veterinary and environmental microbiology. This was made possible through a collaboration with the <a href="https://www.upei.ca/avc" class="external-link">University of Prince Edward Island’s Atlantic Veterinary College</a>, Canada. To celebrate this great improvement of the package, we also updated the package logo to reflect this change.</p>
</div>
<div class="section level3">
<h3 id="breaking-2-1-1-9134">Breaking<a class="anchor" aria-label="anchor" href="#breaking-2-1-1-9134"></a></h3>
<h3 id="breaking-2-1-1-9135">Breaking<a class="anchor" aria-label="anchor" href="#breaking-2-1-1-9135"></a></h3>
<ul><li>Removed all functions and references that used the deprecated <code>rsi</code> class, which were all replaced with their <code>sir</code> equivalents two years ago</li>
</ul></div>
<div class="section level3">
<h3 id="new-2-1-1-9134">New<a class="anchor" aria-label="anchor" href="#new-2-1-1-9134"></a></h3>
<h3 id="new-2-1-1-9135">New<a class="anchor" aria-label="anchor" href="#new-2-1-1-9135"></a></h3>
<ul><li>
<strong>One Health implementation</strong>
<ul><li>Function <code><a href="../reference/as.sir.html">as.sir()</a></code> now has extensive support for veterinary breakpoints from CLSI. Use <code>breakpoint_type = "animal"</code> and set the <code>host</code> argument to a variable that contains animal species names.</li>
@ -109,7 +109,7 @@
</ul></li>
</ul></div>
<div class="section level3">
<h3 id="changed-2-1-1-9134">Changed<a class="anchor" aria-label="anchor" href="#changed-2-1-1-9134"></a></h3>
<h3 id="changed-2-1-1-9135">Changed<a class="anchor" aria-label="anchor" href="#changed-2-1-1-9135"></a></h3>
<ul><li>SIR interpretation
<ul><li>It is now possible to use column names for argument <code>ab</code>, <code>mo</code>, and <code>uti</code>: <code>as.sir(..., ab = "column1", mo = "column2", uti = "column3")</code>. This greatly improves the flexibility for users.</li>
<li>Users can now set their own criteria (using regular expressions) as to what should be considered S, I, R, SDD, and NI.</li>
@ -172,7 +172,7 @@
</ul></li>
</ul></div>
<div class="section level3">
<h3 id="other-2-1-1-9134">Other<a class="anchor" aria-label="anchor" href="#other-2-1-1-9134"></a></h3>
<h3 id="other-2-1-1-9135">Other<a class="anchor" aria-label="anchor" href="#other-2-1-1-9135"></a></h3>
<ul><li>Added Dr. Larisse Bolton as contributor for her fantastic implementation of WISCA in a mathematically solid way</li>
<li>Added Matthew Saab, Dr. Jordan Stull, and Prof. Javier Sanchez as contributors for their tremendous input on veterinary breakpoints and interpretations</li>
<li>Greatly improved <code>vctrs</code> integration, a Tidyverse package working in the background for many Tidyverse functions. For users, this means that functions such as <code>dplyr</code>’s <code><a href="https://dplyr.tidyverse.org/reference/bind_rows.html" class="external-link">bind_rows()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/rowwise.html" class="external-link">rowwise()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/c_across.html" class="external-link">c_across()</a></code> are now supported for e.g. columns of class <code>mic</code>. Despite this, this <code>AMR</code> package is still zero-dependent on any other package, including <code>dplyr</code> and <code>vctrs</code>.</li>
@ -180,7 +180,7 @@
<li>Stopped support for SAS (<code>.xpt</code>) files, since their file structure and extremely inefficient and requires more disk space than GitHub allows in a single commit.</li>
</ul></div>
<div class="section level3">
<h3 id="older-versions-2-1-1-9134">Older Versions<a class="anchor" aria-label="anchor" href="#older-versions-2-1-1-9134"></a></h3>
<h3 id="older-versions-2-1-1-9135">Older Versions<a class="anchor" aria-label="anchor" href="#older-versions-2-1-1-9135"></a></h3>
<p>This changelog only contains changes from AMR v3.0 (February 2025) and later.</p>
<ul><li>For prior v2 versions, please see <a href="https://github.com/msberends/AMR/blob/v2.1.1/NEWS.md" class="external-link">our v2 archive</a>.</li>
<li>For prior v1 versions, please see <a href="https://github.com/msberends/AMR/blob/v1.8.2/NEWS.md" class="external-link">our v1 archive</a>.</li>

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pkgdown.yml
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@ -12,7 +12,7 @@ articles:
resistance_predict: resistance_predict.html
welcome_to_AMR: welcome_to_AMR.html
WHONET: WHONET.html
last_built: 2025-01-27T22:15Z
last_built: 2025-01-28T14:22Z
urls:
reference: https://msberends.github.io/AMR/reference
article: https://msberends.github.io/AMR/articles

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reference/AMR-deprecated.html
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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="">2.1.1.9134</small>
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reference/AMR-options.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/AMR.html
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@ -21,7 +21,7 @@ The AMR package is available in English, Chinese, Czech, Danish, Dutch, Finnish,
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/WHOCC.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/WHONET.html
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@ -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="">2.1.1.9134</small>
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reference/ab_from_text.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/ab_property.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/add_custom_antimicrobials.html
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@ -7,7 +7,7 @@
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reference/age.html
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@ -7,7 +7,7 @@
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@ -111,16 +111,16 @@
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="va">df</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> birth_date age age_exact age_at_y2k</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1 1965-12-05 59 59.14521 34</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 1980-03-01 44 44.90959 19</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 1949-11-01 75 75.23836 50</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 1947-02-14 77 77.95068 52</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 1940-02-19 84 84.93699 59</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 1988-01-10 37 37.04658 11</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 1997-08-27 27 27.41918 2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 1978-01-26 47 47.00274 21</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 1972-06-17 52 52.61370 27</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 1986-08-10 38 38.46575 13</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1 1965-12-05 59 59.14795 34</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 1980-03-01 44 44.91233 19</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 1949-11-01 75 75.24110 50</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 1947-02-14 77 77.95342 52</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 1940-02-19 84 84.93973 59</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 1988-01-10 37 37.04932 11</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 1997-08-27 27 27.42192 2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 1978-01-26 47 47.00548 21</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 1972-06-17 52 52.61644 27</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 1986-08-10 38 38.46849 13</span>
</code></pre></div>
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reference/antibiogram.html
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<!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>Generate Traditional, Combination, Syndromic, or WISCA Antibiograms — antibiogram • 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-6.5.2/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="Generate Traditional, Combination, Syndromic, or WISCA Antibiograms — antibiogram"><meta name="description" content="Create detailed antibiograms with options for traditional, combination, syndromic, and Bayesian WISCA methods.
Adhering to previously described approaches (see Source) and especially the Bayesian WISCA model (Weighted-Incidence Syndromic Combination Antibiogram) by Bielicki et al., these functions provides flexible output formats including plots and tables, ideal for integration with R Markdown and Quarto reports."><meta property="og:description" content="Create detailed antibiograms with options for traditional, combination, syndromic, and Bayesian WISCA methods.
Adhering to previously described approaches (see Source) and especially the Bayesian WISCA model (Weighted-Incidence Syndromic Combination Antibiogram) by Bielicki et al., these functions provides flexible output formats including plots and tables, ideal for integration with R Markdown and Quarto reports."><meta property="og:image" content="https://msberends.github.io/AMR/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>
Adhering to previously described approaches (see Source) and especially the Bayesian WISCA model (Weighted-Incidence Syndromic Combination Antibiogram) by Bielicki et al., these functions provide flexible output formats including plots and tables, ideal for integration with R Markdown and Quarto reports."><meta property="og:description" content="Create detailed antibiograms with options for traditional, combination, syndromic, and Bayesian WISCA methods.
Adhering to previously described approaches (see Source) and especially the Bayesian WISCA model (Weighted-Incidence Syndromic Combination Antibiogram) by Bielicki et al., these functions provide flexible output formats including plots and tables, ideal for integration with R Markdown and Quarto reports."><meta property="og:image" content="https://msberends.github.io/AMR/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>
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@ -9,7 +9,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
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@ -52,7 +52,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
<div class="ref-description section level2">
<p>Create detailed antibiograms with options for traditional, combination, syndromic, and Bayesian WISCA methods.</p>
<p>Adhering to previously described approaches (see <em>Source</em>) and especially the Bayesian WISCA model (Weighted-Incidence Syndromic Combination Antibiogram) by Bielicki <em>et al.</em>, these functions provides flexible output formats including plots and tables, ideal for integration with R Markdown and Quarto reports.</p>
<p>Adhering to previously described approaches (see <em>Source</em>) and especially the Bayesian WISCA model (Weighted-Incidence Syndromic Combination Antibiogram) by Bielicki <em>et al.</em>, these functions provide flexible output formats including plots and tables, ideal for integration with R Markdown and Quarto reports.</p>
</div>
<div class="section level2">
@ -192,8 +192,8 @@ Adhering to previously described approaches (see Source) and especially the Baye
</dl></div>
<div class="section level2">
<h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
<p>This function returns a table with values between 0 and 100 for <em>susceptibility</em>, not resistance.</p>
<p><strong>Remember that you should filter your data to let it contain only first isolates!</strong> This is needed to exclude duplicates and to reduce selection bias. Use <code><a href="first_isolate.html">first_isolate()</a></code> to determine them in your data set with one of the four available algorithms.</p>
<p>These functions return a table with values between 0 and 100 for <em>susceptibility</em>, not resistance.</p>
<p><strong>Remember that you should filter your data to let it contain only first isolates!</strong> This is needed to exclude duplicates and to reduce selection bias. Use <code><a href="first_isolate.html">first_isolate()</a></code> to determine them with one of the four available algorithms: isolate-based, patient-based, episode-based, or phenotype-based.</p>
<p>For estimating antimicrobial coverage, especially when creating a WISCA, the outcome might become more reliable by only including the top <em>n</em> species encountered in the data. You can filter on this top <em>n</em> using <code><a href="top_n_microorganisms.html">top_n_microorganisms()</a></code>. For example, use <code>top_n_microorganisms(your_data, n = 10)</code> as a pre-processing step to only include the top 10 species in the data.</p>
<p>The numeric values of an antibiogram are stored in a long format as the <a href="https://rdrr.io/r/base/attributes.html" class="external-link">attribute</a> <code>long_numeric</code>. You can retrieve them using <code>attributes(x)$long_numeric</code>, where <code>x</code> is the outcome of <code>antibiogram()</code> or <code>wisca()</code>. This is ideal for e.g. advanced plotting.</p><div class="section">
<h3 id="formatting-type">Formatting Type<a class="anchor" aria-label="anchor" href="#formatting-type"></a></h3>
@ -321,7 +321,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
$$p_i = \frac{x_i}{\sum_{j=1}^K x_j}$$</p>
<p>where \(x_i\) represents unnormalised pathogen counts, and \(p_i\) is the normalised proportion for pathogen \(i\).</p>
<p>For hierarchical modelling, pathogen-level effects (e.g., differences in resistance patterns) and regimen-level effects are modelled using Gaussian priors on log-odds. This hierarchical structure ensures partial pooling of estimates across groups, improving stability in strata with small sample sizes. The model is implemented using Hamiltonian Monte Carlo (HMC) sampling.</p>
<p>Stratified results can be provided based on covariates such as age, sex, and clinical complexity (e.g., prior antimicrobial treatments or renal/urological comorbidities) using <code>dplyr</code>'s <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a></code> as a pre-processing step before running <code>wisca()</code>. In this case, posterior odds ratios (ORs) are derived to quantify the effect of these covariates on coverage probabilities:</p>
<p>Stratified results can be provided based on covariates such as age, sex, and clinical complexity (e.g., prior antimicrobial treatments or renal/urological comorbidities) using <code>dplyr</code>'s <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a></code> as a pre-processing step before running <code>wisca()</code>. Posterior odds ratios (ORs) are derived to quantify the effect of these covariates on coverage probabilities:</p>
<p>$$\text{OR}_{\text{covariate}} = \frac{\exp(\beta_{\text{covariate}})}{\exp(\beta_0)}$$</p>
<p>By combining empirical data with prior knowledge, WISCA overcomes the limitations of traditional combination antibiograms, offering disease-specific, patient-stratified estimates with robust uncertainty quantification. This tool is invaluable for antimicrobial stewardship programs and empirical treatment guideline refinement.</p>
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2
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@ -7,7 +7,7 @@
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@ -17,7 +17,7 @@ my_data_with_all_these_columns %&amp;gt;%
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@ -21,7 +21,7 @@ All breakpoints used for interpretation are available in our clinical_breakpoint
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@ -757,16 +757,16 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 57 × 16</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> datetime index ab_given mo_given host_given ab mo </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">*</span> <span style="color: #949494; font-style: italic;">&lt;dttm&gt;</span> <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;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;ab&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 2025-01-27 <span style="color: #949494;">22:16:00</span> 4 genta Escheri… cattle GEN B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 2025-01-27 <span style="color: #949494;">22:16:00</span> 4 genta Escheri… cattle GEN B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 2025-01-27 <span style="color: #949494;">22:16:00</span> 3 tobra Escheri… horses TOB B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 2025-01-27 <span style="color: #949494;">22:16:00</span> 3 tobra Escheri… horses TOB B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 2025-01-27 <span style="color: #949494;">22:16:00</span> 2 cipro Escheri… dogs CIP B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 2025-01-27 <span style="color: #949494;">22:16:00</span> 2 cipro Escheri… dogs CIP B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 2025-01-27 <span style="color: #949494;">22:16:01</span> 2 nitrofu… E. coli human NIT B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 2025-01-27 <span style="color: #949494;">22:16:02</span> 2 nitrofu… E. coli human NIT B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 2025-01-27 <span style="color: #949494;">22:16:00</span> 1 tobra bacteria human TOB B_[KNG]_BACTERIA</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 2025-01-27 <span style="color: #949494;">22:16:00</span> 1 genta bacteria human GEN B_[KNG]_BACTERIA</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 2025-01-28 <span style="color: #949494;">14:23:05</span> 4 AMX B_STRPT… human AMX B_STRPT_PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 2025-01-28 <span style="color: #949494;">14:23:12</span> 4 genta Escheri… human GEN B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 2025-01-28 <span style="color: #949494;">14:23:12</span> 4 genta Escheri… human GEN B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 2025-01-28 <span style="color: #949494;">14:23:13</span> 4 genta Escheri… cattle GEN B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 2025-01-28 <span style="color: #949494;">14:23:13</span> 4 genta Escheri… cattle GEN B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 2025-01-28 <span style="color: #949494;">14:23:05</span> 3 AMX B_STRPT… human AMX B_STRPT_PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 2025-01-28 <span style="color: #949494;">14:23:12</span> 3 tobra Escheri… human TOB B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 2025-01-28 <span style="color: #949494;">14:23:12</span> 3 tobra Escheri… human TOB B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 2025-01-28 <span style="color: #949494;">14:23:13</span> 3 tobra Escheri… horses TOB B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 2025-01-28 <span style="color: #949494;">14:23:13</span> 3 tobra Escheri… horses TOB B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 47 more rows</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 9 more variables: host &lt;chr&gt;, method &lt;chr&gt;, input &lt;dbl&gt;, outcome &lt;sir&gt;,</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># notes &lt;chr&gt;, guideline &lt;chr&gt;, ref_table &lt;chr&gt;, uti &lt;lgl&gt;,</span></span>

2
reference/atc_online.html
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@ -7,7 +7,7 @@
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reference/availability.html
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reference/clinical_breakpoints.html
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@ -21,7 +21,7 @@ Use as.sir() to transform MICs or disks measurements to SIR values."><meta prope
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@ -9,7 +9,7 @@ count_resistant() should be used to count resistant isolates, count_susceptible(
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@ -9,7 +9,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
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@ -9,7 +9,7 @@ This data set is carefully crafted, yet made 100% reproducible from public and a
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@ -9,7 +9,7 @@ This is the fastest way to have your organisation (or analysis) specific codes p
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@ -9,7 +9,7 @@ Especially the scale_*_mic() functions are relevant wrappers to plot MIC values
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reference/proportion.html
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@ -9,7 +9,7 @@ resistance() should be used to calculate resistance, susceptibility() should be
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@ -7,7 +7,7 @@
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reference/resistance_predict.html
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@ -7,7 +7,7 @@
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reference/skewness.html
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@ -9,7 +9,7 @@ When negative ('left-skewed'): the left tail is longer; the mass of the distribu
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search.json
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