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@@ -31,7 +31,7 @@
<a class="navbar-brand me-2" href="https://amr-for-r.org/index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

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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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

10
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@@ -30,7 +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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">
@@ -91,7 +91,7 @@
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 03 September 2025.</p>
generated on 10 September 2025.</p>
<div class="section level2">
<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
</h2>
@@ -147,21 +147,21 @@ make the structure of your data generally look like this:</p>
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2025-09-03</td>
<td align="center">2025-09-10</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">2025-09-03</td>
<td align="center">2025-09-10</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">2025-09-03</td>
<td align="center">2025-09-10</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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@@ -30,7 +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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</small>
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284
articles/AMR_with_tidymodels.html
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@@ -30,7 +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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">
@@ -438,239 +438,21 @@ and reproducibly.</p>
<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><a href="../reference/amr-tidymodels.html">step_mic_log2()</a></code>, which prepares MIC values for use in
<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>
<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>Use raw MIC values to predict whether a bacterial isolate produces
ESBL.</li>
<li>Apply AMR-aware preprocessing in a <code>tidymodels</code>
recipe.</li>
<li>Train a classification model and evaluate its predictive
performance.</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 use the <code>esbl_isolates</code> dataset that comes with the AMR
package.</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"># View the esbl_isolates data set</span></span>
<span><span class="va">esbl_isolates</span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 500 × 19</span></span></span>
<span><span class="co">#&gt; esbl genus AMC AMP TZP CXM FOX CTX CAZ GEN TOB TMP SXT</span></span>
<span><span class="co">#&gt; <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span></span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 1</span> FALSE Esch… 32 32 4 64 64 8<span style="color: #BBBBBB;">.00</span> 8<span style="color: #BBBBBB;">.00</span> 1 1 16<span style="color: #BBBBBB;">.0</span> 20</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 2</span> FALSE Esch… 32 32 4 64 64 4<span style="color: #BBBBBB;">.00</span> 8<span style="color: #BBBBBB;">.00</span> 1 1 16<span style="color: #BBBBBB;">.0</span> 320</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 3</span> FALSE Esch… 4 2 64 8 4 8<span style="color: #BBBBBB;">.00</span> 0.12 16 16 0.5 20</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 4</span> FALSE Kleb… 32 32 16 64 64 8<span style="color: #BBBBBB;">.00</span> 8<span style="color: #BBBBBB;">.00</span> 1 1 0.5 20</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 5</span> FALSE Esch… 32 32 4 4 4 0.25 2<span style="color: #BBBBBB;">.00</span> 1 1 16<span style="color: #BBBBBB;">.0</span> 320</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 6</span> FALSE Citr… 32 32 16 64 64 64<span style="color: #BBBBBB;">.00</span> 32<span style="color: #BBBBBB;">.00</span> 1 1 0.5 20</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 7</span> FALSE Morg… 32 32 4 64 64 16<span style="color: #BBBBBB;">.00</span> 2<span style="color: #BBBBBB;">.00</span> 1 1 0.5 20</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> FALSE Prot… 16 32 4 1 4 8<span style="color: #BBBBBB;">.00</span> 0.12 1 1 16<span style="color: #BBBBBB;">.0</span> 320</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> FALSE Ente… 32 32 8 64 64 32<span style="color: #BBBBBB;">.00</span> 4<span style="color: #BBBBBB;">.00</span> 1 1 0.5 20</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> FALSE Citr… 32 32 32 64 64 8<span style="color: #BBBBBB;">.00</span> 64<span style="color: #BBBBBB;">.00</span> 1 1 16<span style="color: #BBBBBB;">.0</span> 320</span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 490 more rows</span></span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 6 more variables: NIT &lt;mic&gt;, FOS &lt;mic&gt;, CIP &lt;mic&gt;, IPM &lt;mic&gt;, MEM &lt;mic&gt;,</span></span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># COL &lt;mic&gt;</span></span></span>
<span></span>
<span><span class="co"># Prepare a binary outcome and convert to ordered factor</span></span>
<span><span class="va">data</span> <span class="op">&lt;-</span> <span class="va">esbl_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/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>esbl <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a></span><span class="op">(</span><span class="va">esbl</span>, levels <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="cn">FALSE</span>, <span class="cn">TRUE</span><span class="op">)</span>, ordered <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
<p><strong>Explanation:</strong></p>
<ul>
<li>
<code>esbl_isolates</code>: Contains MIC test results and ESBL
status for each isolate.</li>
<li>
<code>mutate(esbl = ...)</code>: Converts the target column to an
ordered factor for classification.</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>
<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>
<p>We use our <code><a href="../reference/amr-tidymodels.html">step_mic_log2()</a></code> function to log2-transform
MIC values, ensuring that MICs are numeric and properly scaled. All MIC
predictors can easily and agnostically selected using the new
<code><a href="../reference/amr-tidymodels.html">all_mic_predictors()</a></code>:</p>
<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="co"># Split 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>
<span><span class="va">split</span> <span class="op">&lt;-</span> <span class="fu">initial_split</span><span class="op">(</span><span class="va">data</span><span class="op">)</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">split</span><span class="op">)</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">split</span><span class="op">)</span></span>
<span></span>
<span><span class="co"># Define the recipe</span></span>
<span><span class="va">mic_recipe</span> <span class="op">&lt;-</span> <span class="fu">recipe</span><span class="op">(</span><span class="va">esbl</span> <span class="op">~</span> <span class="va">.</span>, data <span class="op">=</span> <span class="va">training_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">remove_role</span><span class="op">(</span><span class="va">genus</span>, old_role <span class="op">=</span> <span class="st">"predictor"</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"># Remove non-informative variable</span></span>
<span> <span class="fu"><a href="../reference/amr-tidymodels.html">step_mic_log2</a></span><span class="op">(</span><span class="fu"><a href="../reference/amr-tidymodels.html">all_mic_predictors</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="co">#%&gt;% # Log2 transform all MIC predictors</span></span>
<span> <span class="co"># prep()</span></span>
<span></span>
<span><span class="va">mic_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: 17</span></span>
<span><span class="co">#&gt; undeclared role: 1</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> Log2 transformation of MIC columns: <span style="color: #0000BB;">all_mic_predictors()</span></span></span></code></pre></div>
<p><strong>Explanation:</strong></p>
<ul>
<li>
<code>remove_role()</code>: Removes irrelevant variables like
genus.</li>
<li>
<code><a href="../reference/amr-tidymodels.html">step_mic_log2()</a></code>: Applies
<code>log2(as.numeric(...))</code> to all MIC predictors in one go.</li>
<li>
<code>prep()</code>: Finalises the recipe based on training
data.</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 simple logistic regression to model ESBL presence, though
recent models such as xgboost (<a href="https://parsnip.tidymodels.org/reference/details_boost_tree_xgboost.html" class="external-link">link
to <code>parsnip</code> manual</a>) could be much more precise.</p>
<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="co"># Define the model</span></span>
<span><span class="va">model</span> <span class="op">&lt;-</span> <span class="fu">logistic_reg</span><span class="op">(</span>mode <span class="op">=</span> <span class="st">"classification"</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>
<span></span>
<span><span class="va">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>: Specifies a binary classification
model.</li>
<li>
<code>set_engine("glm")</code>: Uses the base R GLM 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>
<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">workflow_model</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">mic_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>
<span> <span class="fu">add_model</span><span class="op">(</span><span class="va">model</span><span class="op">)</span></span>
<span></span>
<span><span class="va">workflow_model</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_mic_log2()</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-1">
<strong>Training and Evaluating the Model</strong><a class="anchor" aria-label="anchor" href="#training-and-evaluating-the-model-1"></a>
</h3>
<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="co"># Fit the model</span></span>
<span><span class="va">fitted</span> <span class="op">&lt;-</span> <span class="fu">fit</span><span class="op">(</span><span class="va">workflow_model</span>, <span class="va">training_data</span><span class="op">)</span></span>
<span></span>
<span><span class="co"># Generate predictions</span></span>
<span><span class="va">predictions</span> <span class="op">&lt;-</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">fitted</span>, <span class="va">testing_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"><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>
<span></span>
<span><span class="co"># Evaluate model performance</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>
<span><span class="va">metrics</span> <span class="op">&lt;-</span> <span class="fu">our_metrics</span><span class="op">(</span><span class="va">predictions</span>, truth <span class="op">=</span> <span class="va">esbl</span>, estimate <span class="op">=</span> <span class="va">.pred_class</span><span class="op">)</span></span>
<span></span>
<span><span class="va">metrics</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 0.92 </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> kap binary 0.840</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> ppv binary 0.921</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> npv binary 0.919</span></span></code></pre></div>
<p><strong>Explanation:</strong></p>
<ul>
<li>
<code>fit()</code>: Trains the model on the processed training
data.</li>
<li>
<code><a href="https://rdrr.io/r/stats/predict.html" class="external-link">predict()</a></code>: Produces predictions for unseen test
data.</li>
<li>
<code>metric_set()</code>: Allows evaluating multiple classification
metrics.</li>
</ul>
<p>It appears we can predict ESBL gene presence with a positive
predictive value (PPV) of 92.1% and a negative predictive value (NPV) of
91.9 using a simplistic logistic regression model.</p>
</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 can visualise predictions by comparing predicted and actual ESBL
status.</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="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">predictions</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">esbl</span>, fill <span class="op">=</span> <span class="va">.pred_class</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_bar.html" class="external-link">geom_bar</a></span><span class="op">(</span>position <span class="op">=</span> <span class="st">"stack"</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 ESBL Status"</span>,</span>
<span> x <span class="op">=</span> <span class="st">"Actual ESBL"</span>,</span>
<span> y <span class="op">=</span> <span class="st">"Count"</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>
</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 showcased how the new <code>AMR</code>-specific
recipe steps simplify working with <code>&lt;mic&gt;</code> columns in
<code>tidymodels</code>. The <code><a href="../reference/amr-tidymodels.html">step_mic_log2()</a></code> transformation
converts ordered MICs to log2-transformed numerics, improving
compatibility with classification models.</p>
<p>This pipeline enables realistic, reproducible, and interpretable
modelling of antimicrobial resistance data.</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>
<div class="section level2">
<h2 id="example-3-predicting-amr-over-time">Example 3: Predicting AMR Over Time<a class="anchor" aria-label="anchor" href="#example-3-predicting-amr-over-time"></a>
<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
@@ -679,8 +461,8 @@ 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-2">
<strong>Objective</strong><a class="anchor" aria-label="anchor" href="#objective-2"></a>
<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">
@@ -691,12 +473,12 @@ model.</li>
</ol>
</div>
<div class="section level3">
<h3 id="data-preparation-2">
<strong>Data Preparation</strong><a class="anchor" aria-label="anchor" href="#data-preparation-2"></a>
<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="cb16"><pre class="downlit sourceCode r">
<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>
@@ -743,15 +525,15 @@ rates by year and ward.</li>
</ul>
</div>
<div class="section level3">
<h3 id="defining-the-workflow-2">
<strong>Defining the Workflow</strong><a class="anchor" aria-label="anchor" href="#defining-the-workflow-2"></a>
<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-2">1. Preprocessing with a Recipe<a class="anchor" aria-label="anchor" href="#preprocessing-with-a-recipe-2"></a>
<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="cb17"><pre class="downlit sourceCode r">
<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>
@@ -784,10 +566,10 @@ variable.</li>
</ul>
</div>
<div class="section level4">
<h4 id="specifying-the-model-2">2. Specifying the Model<a class="anchor" aria-label="anchor" href="#specifying-the-model-2"></a>
<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="cb18"><pre class="downlit sourceCode r">
<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>
@@ -806,10 +588,10 @@ engine.</li>
</ul>
</div>
<div class="section level4">
<h4 id="building-the-workflow-2">3. Building the Workflow<a class="anchor" aria-label="anchor" href="#building-the-workflow-2"></a>
<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="cb19"><pre class="downlit sourceCode r">
<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>
@@ -834,12 +616,12 @@ engine.</li>
</div>
</div>
<div class="section level3">
<h3 id="training-and-evaluating-the-model-2">
<strong>Training and Evaluating the Model</strong><a class="anchor" aria-label="anchor" href="#training-and-evaluating-the-model-2"></a>
<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="cb20"><pre class="downlit sourceCode r">
<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>
@@ -880,11 +662,11 @@ sets.</li>
</ul>
</div>
<div class="section level3">
<h3 id="visualising-predictions-1">
<strong>Visualising Predictions</strong><a class="anchor" aria-label="anchor" href="#visualising-predictions-1"></a>
<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="cb21"><pre class="downlit sourceCode r">
<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>
@@ -895,10 +677,10 @@ sets.</li>
<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-20-1.png" width="720"></p>
<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="cb22"><pre class="downlit sourceCode r">
<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>
@@ -909,11 +691,11 @@ sets.</li>
<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-21-1.png" width="720"></p>
<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-2">
<strong>Conclusion</strong><a class="anchor" aria-label="anchor" href="#conclusion-2"></a>
<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

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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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

2
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@@ -30,7 +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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

2
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@@ -30,7 +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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

2
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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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

4
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@@ -30,7 +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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">
@@ -80,7 +80,7 @@
<main id="main" class="col-md-9"><div class="page-header">
<img src="../logo.svg" class="logo" alt=""><h1>Download data sets for download / own use</h1>
<h4 data-toc-skip class="date">03 September 2025</h4>
<h4 data-toc-skip class="date">10 September 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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<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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

2
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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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

2
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@@ -33,7 +33,7 @@
<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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

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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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">
@@ -48,40 +48,6 @@
<small>Source: <a href="https://github.com/msberends/AMR/blob/main/NEWS.md" class="external-link"><code>NEWS.md</code></a></small>
</div>
<div class="section level2">
<h2 class="pkg-version" data-toc-text="3.0.0.9021" id="amr-3009021">AMR 3.0.0.9021<a class="anchor" aria-label="anchor" href="#amr-3009021"></a></h2>
<p>This is primarily a bugfix release, though we added one nice feature too.</p>
<div class="section level4">
<h4 id="new-3-0-0-9021">New<a class="anchor" aria-label="anchor" href="#new-3-0-0-9021"></a></h4>
<ul><li>Integration with the <strong>tidymodels</strong> framework to allow seamless use of MIC and SIR data in modelling pipelines via <code>recipes</code>
<ul><li>
<code><a href="../reference/amr-tidymodels.html">step_mic_log2()</a></code> to transform <code>&lt;mic&gt;</code> columns with log2, and <code><a href="../reference/amr-tidymodels.html">step_sir_numeric()</a></code> to convert <code>&lt;sir&gt;</code> columns to numeric</li>
<li>New <code>tidyselect</code> helpers: <code><a href="../reference/amr-tidymodels.html">all_mic()</a></code>, <code><a href="../reference/amr-tidymodels.html">all_mic_predictors()</a></code>, <code><a href="../reference/amr-tidymodels.html">all_sir()</a></code>, <code><a href="../reference/amr-tidymodels.html">all_sir_predictors()</a></code>
</li>
</ul></li>
</ul></div>
<div class="section level4">
<h4 id="changed-3-0-0-9021">Changed<a class="anchor" aria-label="anchor" href="#changed-3-0-0-9021"></a></h4>
<ul><li>Fixed a bug in <code><a href="../reference/antibiogram.html">antibiogram()</a></code> for when no antimicrobials are set</li>
<li>Fixed a bug in <code><a href="../reference/antibiogram.html">antibiogram()</a></code> to allow column names containing the <code>+</code> character (<a href="https://github.com/msberends/AMR/issues/222" class="external-link">#222</a>)</li>
<li>Fixed a bug in <code><a href="../reference/as.ab.html">as.ab()</a></code> for antimicrobial codes with a number in it if they are preceded by a space</li>
<li>Fixed a bug in <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> for using specific custom rules</li>
<li>Fixed a bug in <code><a href="../reference/as.sir.html">as.sir()</a></code> to allow any tidyselect language (<a href="https://github.com/msberends/AMR/issues/220" class="external-link">#220</a>)</li>
<li>Fixed a bug in <code><a href="../reference/as.sir.html">as.sir()</a></code> to pick right breakpoint when <code>uti = FALSE</code> (<a href="https://github.com/msberends/AMR/issues/216" class="external-link">#216</a>)</li>
<li>Fixed a bug in <code><a href="../reference/ggplot_sir.html">ggplot_sir()</a></code> when using <code>combine_SI = FALSE</code> (<a href="https://github.com/msberends/AMR/issues/213" class="external-link">#213</a>)</li>
<li>Fixed a bug the <code>antimicrobials</code> data set to remove statins (<a href="https://github.com/msberends/AMR/issues/229" class="external-link">#229</a>)</li>
<li>Fixed a bug in <code><a href="../reference/mdro.html">mdro()</a></code> to make sure all genes specified in arguments are acknowledges</li>
<li>Fixed ATC J01CR05 to map to piperacillin/tazobactam rather than piperacillin/sulbactam (<a href="https://github.com/msberends/AMR/issues/230" class="external-link">#230</a>)</li>
<li>Fixed all plotting to contain a separate colour for SDD (susceptible dose-dependent) (<a href="https://github.com/msberends/AMR/issues/223" class="external-link">#223</a>)</li>
<li>Fixed some specific Dutch translations for antimicrobials</li>
<li>Added all reasons in verbose output of <code><a href="../reference/mdro.html">mdro()</a></code> (<a href="https://github.com/msberends/AMR/issues/227" class="external-link">#227</a>)</li>
<li>Added <code>names</code> to <code><a href="../reference/age_groups.html">age_groups()</a></code> so that custom names can be given (<a href="https://github.com/msberends/AMR/issues/215" class="external-link">#215</a>)</li>
<li>Added note to <code><a href="../reference/as.sir.html">as.sir()</a></code> to make it explicit when higher-level taxonomic breakpoints are used (<a href="https://github.com/msberends/AMR/issues/218" class="external-link">#218</a>)</li>
<li>Added antibiotic codes from the Comprehensive Antibiotic Resistance Database (CARD) to the <code>antimicrobials</code> data set (<a href="https://github.com/msberends/AMR/issues/225" class="external-link">#225</a>)</li>
<li>Updated Fosfomycin to be of antibiotic class ‘Phosphonics’ (<a href="https://github.com/msberends/AMR/issues/225" class="external-link">#225</a>)</li>
<li>Updated <code><a href="../reference/random.html">random_mic()</a></code> and <code><a href="../reference/random.html">random_disk()</a></code> to set skewedness of the distribution and allow multiple microorganisms</li>
</ul></div>
</div>
<div class="section level2">
<h2 class="pkg-version" data-toc-text="3.0.0" id="amr-300">AMR 3.0.0<a class="anchor" aria-label="anchor" href="#amr-300"></a></h2><p class="text-muted">CRAN release: 2025-06-02</p>
<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>

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@@ -10,7 +10,7 @@ articles:
PCA: PCA.html
WHONET: WHONET.html
WISCA: WISCA.html
last_built: 2025-09-03T10:17Z
last_built: 2025-09-10T14:26Z
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@@ -7,7 +7,7 @@
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@@ -7,7 +7,7 @@
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@@ -112,16 +112,16 @@
<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 1980-02-27 45 45.51507 19</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 1953-07-26 72 72.10685 46</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 1949-09-02 76 76.00274 50</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 1986-08-03 39 39.08493 13</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 1932-11-19 92 92.78904 67</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 1949-03-30 76 76.43014 50</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 1996-06-23 29 29.19726 3</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 1963-09-16 61 61.96438 36</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 1952-05-16 73 73.30137 47</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 1952-11-14 72 72.80274 47</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1 1980-02-27 45 45.53425 19</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 1953-07-26 72 72.12603 46</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 1949-09-02 76 76.02192 50</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 1986-08-03 39 39.10411 13</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 1932-11-19 92 92.80822 67</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 1949-03-30 76 76.44932 50</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 1996-06-23 29 29.21644 3</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 1963-09-16 61 61.98356 36</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 1952-05-16 73 73.32055 47</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 1952-11-14 72 72.82192 47</span>
</code></pre></div>
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</div>
<div class="ref-description section level2">
<p>This family of functions allows using AMR-specific data types such as <code>&lt;mic&gt;</code> and <code>&lt;sir&gt;</code> inside <code>tidymodels</code> pipelines.</p>
</div>
<div class="section level2">
<h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
<div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">all_mic</span><span class="op">(</span><span class="op">)</span></span>
<span></span>
<span><span class="fu">all_mic_predictors</span><span class="op">(</span><span class="op">)</span></span>
<span></span>
<span><span class="fu">all_sir</span><span class="op">(</span><span class="op">)</span></span>
<span></span>
<span><span class="fu">all_sir_predictors</span><span class="op">(</span><span class="op">)</span></span>
<span></span>
<span><span class="fu">step_mic_log2</span><span class="op">(</span><span class="va">recipe</span>, <span class="va">...</span>, role <span class="op">=</span> <span class="cn">NA</span>, trained <span class="op">=</span> <span class="cn">FALSE</span>, columns <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> skip <span class="op">=</span> <span class="cn">FALSE</span>, id <span class="op">=</span> <span class="fu">recipes</span><span class="fu">::</span><span class="fu"><a href="https://recipes.tidymodels.org/reference/rand_id.html" class="external-link">rand_id</a></span><span class="op">(</span><span class="st">"mic_log2"</span><span class="op">)</span><span class="op">)</span></span>
<span></span>
<span><span class="fu">step_sir_numeric</span><span class="op">(</span><span class="va">recipe</span>, <span class="va">...</span>, role <span class="op">=</span> <span class="cn">NA</span>, trained <span class="op">=</span> <span class="cn">FALSE</span>, columns <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> skip <span class="op">=</span> <span class="cn">FALSE</span>, id <span class="op">=</span> <span class="fu">recipes</span><span class="fu">::</span><span class="fu"><a href="https://recipes.tidymodels.org/reference/rand_id.html" class="external-link">rand_id</a></span><span class="op">(</span><span class="st">"sir_numeric"</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
</div>
<div class="section level2">
<h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
<dl><dt id="arg-recipe">recipe<a class="anchor" aria-label="anchor" href="#arg-recipe"></a></dt>
<dd><p>A recipe object. The step will be added to the sequence of
operations for this recipe.</p></dd>
<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
<dd><p>One or more selector functions to choose variables for this step.
See <code><a href="https://recipes.tidymodels.org/reference/selections.html" class="external-link">selections()</a></code> for more details.</p></dd>
<dt id="arg-role">role<a class="anchor" aria-label="anchor" href="#arg-role"></a></dt>
<dd><p>Not used by this step since no new variables are created.</p></dd>
<dt id="arg-trained">trained<a class="anchor" aria-label="anchor" href="#arg-trained"></a></dt>
<dd><p>A logical to indicate if the quantities for preprocessing have
been estimated.</p></dd>
<dt id="arg-skip">skip<a class="anchor" aria-label="anchor" href="#arg-skip"></a></dt>
<dd><p>A logical. Should the step be skipped when the recipe is baked by
<code><a href="https://recipes.tidymodels.org/reference/bake.html" class="external-link">bake()</a></code>? While all operations are baked when <code><a href="https://recipes.tidymodels.org/reference/prep.html" class="external-link">prep()</a></code> is run, some
operations may not be able to be conducted on new data (e.g. processing the
outcome variable(s)). Care should be taken when using <code>skip = TRUE</code> as it
may affect the computations for subsequent operations.</p></dd>
<dt id="arg-id">id<a class="anchor" aria-label="anchor" href="#arg-id"></a></dt>
<dd><p>A character string that is unique to this step to identify it.</p></dd>
</dl></div>
<div class="section level2">
<h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
<p>You can read more in our online <a href="https://amr-for-r.org/articles/AMR_with_tidymodels.html">AMR with tidymodels introduction</a>.</p>
<p>Tidyselect helpers include:</p><ul><li><p><code>all_mic()</code> and <code>all_mic_predictors()</code> to select <code>&lt;mic&gt;</code> columns</p></li>
<li><p><code>all_sir()</code> and <code>all_sir_predictors()</code> to select <code>&lt;sir&gt;</code> columns</p></li>
</ul><p>Pre-processing pipeline steps include:</p><ul><li><p><code>step_mic_log2()</code> to convert MIC columns to numeric (via <code><a href="https://rdrr.io/r/base/numeric.html" class="external-link">as.numeric()</a></code>) and apply a log2 transform, to be used with <code>all_mic_predictors()</code></p></li>
<li><p><code>step_sir_numeric()</code> to convert SIR columns to numeric (via <code><a href="https://rdrr.io/r/base/numeric.html" class="external-link">as.numeric()</a></code>), to be used with <code>all_sir_predictors()</code>: <code>"S"</code> = 1, <code>"I"</code>/<code>"SDD"</code> = 2, <code>"R"</code> = 3. All other values are rendered <code>NA</code>. Keep this in mind for further processing, especially if the model does not allow for <code>NA</code> values.</p></li>
</ul><p>These steps integrate with <code><a href="https://recipes.tidymodels.org/reference/recipe.html" class="external-link">recipes::recipe()</a></code> and work like standard preprocessing steps. They are useful for preparing data for modelling, especially with classification models.</p>
</div>
<div class="section level2">
<h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
<div class="dont-index"><p><code><a href="https://recipes.tidymodels.org/reference/recipe.html" class="external-link">recipes::recipe()</a></code>, <code><a href="as.mic.html">as.mic()</a></code>, <code><a href="as.sir.html">as.sir()</a></code></p></div>
</div>
<div class="section level2">
<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://tidymodels.tidymodels.org" class="external-link">"tidymodels"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># The below approach formed the basis for this paper: DOI 10.3389/fmicb.2025.1582703</span></span></span>
<span class="r-in"><span> <span class="co"># Presence of ESBL genes was predicted based on raw MIC values.</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># example data set in the AMR package</span></span></span>
<span class="r-in"><span> <span class="va">esbl_isolates</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Prepare a binary outcome and convert to ordered factor</span></span></span>
<span class="r-in"><span> <span class="va">data</span> <span class="op">&lt;-</span> <span class="va">esbl_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>esbl <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a></span><span class="op">(</span><span class="va">esbl</span>, levels <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="cn">FALSE</span>, <span class="cn">TRUE</span><span class="op">)</span>, ordered <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Split into training and testing sets</span></span></span>
<span class="r-in"><span> <span class="va">split</span> <span class="op">&lt;-</span> <span class="fu">initial_split</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></span>
<span class="r-in"><span> <span class="va">training_data</span> <span class="op">&lt;-</span> <span class="fu">training</span><span class="op">(</span><span class="va">split</span><span class="op">)</span></span></span>
<span class="r-in"><span> <span class="va">testing_data</span> <span class="op">&lt;-</span> <span class="fu">testing</span><span class="op">(</span><span class="va">split</span><span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Create and prep a recipe with MIC log2 transformation</span></span></span>
<span class="r-in"><span> <span class="va">mic_recipe</span> <span class="op">&lt;-</span> <span class="fu">recipe</span><span class="op">(</span><span class="va">esbl</span> <span class="op">~</span> <span class="va">.</span>, data <span class="op">=</span> <span class="va">training_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="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Optionally remove non-predictive variables</span></span></span>
<span class="r-in"><span> <span class="fu">remove_role</span><span class="op">(</span><span class="va">genus</span>, old_role <span class="op">=</span> <span class="st">"predictor"</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="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Apply the log2 transformation to all MIC predictors</span></span></span>
<span class="r-in"><span> <span class="fu">step_mic_log2</span><span class="op">(</span><span class="fu">all_mic_predictors</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="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># And apply the preparation steps</span></span></span>
<span class="r-in"><span> <span class="fu">prep</span><span class="op">(</span><span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># View prepped recipe</span></span></span>
<span class="r-in"><span> <span class="va">mic_recipe</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Apply the recipe to training and testing data</span></span></span>
<span class="r-in"><span> <span class="va">out_training</span> <span class="op">&lt;-</span> <span class="fu">bake</span><span class="op">(</span><span class="va">mic_recipe</span>, new_data <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span></span></span>
<span class="r-in"><span> <span class="va">out_testing</span> <span class="op">&lt;-</span> <span class="fu">bake</span><span class="op">(</span><span class="va">mic_recipe</span>, new_data <span class="op">=</span> <span class="va">testing_data</span><span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Fit a logistic regression model</span></span></span>
<span class="r-in"><span> <span class="va">fitted</span> <span class="op">&lt;-</span> <span class="fu">logistic_reg</span><span class="op">(</span>mode <span class="op">=</span> <span class="st">"classification"</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="r-in"><span> <span class="fu">set_engine</span><span class="op">(</span><span class="st">"glm"</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="r-in"><span> <span class="fu">fit</span><span class="op">(</span><span class="va">esbl</span> <span class="op">~</span> <span class="va">.</span>, data <span class="op">=</span> <span class="va">out_training</span><span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Generate predictions on the test set</span></span></span>
<span class="r-in"><span> <span class="va">predictions</span> <span class="op">&lt;-</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">fitted</span>, <span class="va">out_testing</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="r-in"><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">out_testing</span><span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Evaluate predictions using standard classification metrics</span></span></span>
<span class="r-in"><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></span>
<span class="r-in"><span> <span class="va">metrics</span> <span class="op">&lt;-</span> <span class="fu">our_metrics</span><span class="op">(</span><span class="va">predictions</span>, truth <span class="op">=</span> <span class="va">esbl</span>, estimate <span class="op">=</span> <span class="va">.pred_class</span><span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Show performance</span></span></span>
<span class="r-in"><span> <span class="va">metrics</span></span></span>
<span class="r-in"><span><span class="op">}</span></span></span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> Loading required package: tidymodels</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> ── <span style="font-weight: bold;">Attaching packages</span> ────────────────────────────────────── tidymodels 1.3.0 ──</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">broom </span> 1.0.9 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">rsample </span> 1.3.1</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">dials </span> 1.4.1 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">tibble </span> 3.3.0</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">infer </span> 1.0.9 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">tidyr </span> 1.3.1</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">modeldata </span> 1.5.1 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">tune </span> 2.0.0</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">parsnip </span> 1.3.3 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">workflows </span> 1.3.0</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">purrr </span> 1.1.0 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">workflowsets</span> 1.1.1</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">recipes </span> 1.3.1 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">yardstick </span> 1.3.2</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> ── <span style="font-weight: bold;">Conflicts</span> ───────────────────────────────────────── tidymodels_conflicts() ──</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #BB0000;">✖</span> <span style="color: #0000BB;">purrr</span>::<span style="color: #00BB00;">discard()</span> masks <span style="color: #0000BB;">scales</span>::discard()</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <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 class="r-msg co"><span class="r-pr">#&gt;</span> <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 class="r-msg co"><span class="r-pr">#&gt;</span> <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 class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>glm.fit: fitted probabilities numerically 0 or 1 occurred</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 4 × 3</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> .metric .estimator .estimate</span>
<span class="r-out co"><span class="r-pr">#&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;dbl&gt;</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> accuracy binary 0.936</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> kap binary 0.872</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> ppv binary 0.925</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> npv binary 0.948</span>
</code></pre></div>
</div>
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14
reference/antibiogram.html
View File

@@ -9,7 +9,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
<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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">
@@ -587,9 +587,9 @@ Adhering to previously described approaches (see Source) and especially the Baye
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Type: WISCA with 95% CI</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> `Syndromic Group` `Piperacillin/tazobactam` Piperacillin/tazobactam + Gentam…¹</span>
<span class="r-out co"><span class="r-pr">#&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>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Clinical 73.6% (68.3-78.8%) 92.3% (90.8-93.8%) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> ICU 57.2% (49.8-65.1%) 84.9% (81.8-87.8%) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> Outpatient 57.1% (47.2-66.8%) 74.4% (69-79.6%) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Clinical 73.4% (67.6-78.6%) 92.4% (90.6-93.7%) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> ICU 57.4% (49.7-65.6%) 85% (82.1-87.6%) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> Outpatient 56.9% (46.9-66.7%) 74.4% (69-79.7%) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ abbreviated name: ¹​`Piperacillin/tazobactam + Gentamicin`</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 1 more variable: `Piperacillin/tazobactam + Tobramycin` &lt;chr&gt;</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,</span></span>
@@ -614,9 +614,9 @@ Adhering to previously described approaches (see Source) and especially the Baye
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> |Syndromic Group |Piperacillin/tazobactam |</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> |:---------------|:-----------------------|</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> |Clinical |73.4% (67.8-78.8%) |</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> |ICU |57.2% (49.6-65.3%) |</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> |Outpatient |56.9% (47.1-66.9%) |</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> |Clinical |73.6% (68.4-79%) |</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> |ICU |57.4% (49.7-65.4%) |</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> |Outpatient |57% (47.2-66.7%) |</span>
<span class="r-in"><span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># Generate plots with ggplot2 or base R --------------------------------</span></span></span>

5
reference/antimicrobial_selectors.html
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@@ -17,7 +17,7 @@ my_data_with_all_these_columns %&amp;gt;%
<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="">3.0.0.9021</small>
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@@ -670,9 +670,6 @@ my_data_with_all_these_columns %&amp;gt;%
<span class="r-msg co"><span class="r-pr">#&gt;</span> Loading required package: data.table</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> Attaching package: ‘data.table’</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> The following object is masked from ‘package:purrr’:</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> transpose</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> The following objects are masked from ‘package:dplyr’:</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> between, first, last</span>

2
reference/antimicrobials.html
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@@ -9,7 +9,7 @@ The antibiotics data set has been renamed to antimicrobials. The old name will b
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reference/as.ab.html
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@@ -7,7 +7,7 @@
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reference/as.av.html
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@@ -7,7 +7,7 @@
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reference/as.disk.html
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@@ -7,7 +7,7 @@
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reference/as.mic.html
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@@ -7,7 +7,7 @@
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2
reference/as.mo.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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12
reference/as.sir.html
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@@ -9,7 +9,7 @@ Breakpoints are currently implemented from EUCAST 2011-2025 and CLSI 2011-2025,
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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@@ -415,10 +415,10 @@ Breakpoints are currently implemented from EUCAST 2011-2025 and CLSI 2011-2025,
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 4 × 18</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> datetime index method ab_given mo_given host_given input_given</span>
<span class="r-out co"><span class="r-pr">#&gt;</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;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> 2025-09-03 <span style="color: #949494;">10:18:07</span> 1 MIC amoxicillin Escherich… human 8 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> 2025-09-03 <span style="color: #949494;">10:18:07</span> 1 MIC cipro Escherich… human 0.256 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> 2025-09-03 <span style="color: #949494;">10:18:07</span> 1 DISK tobra Escherich… human 16 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> 2025-09-03 <span style="color: #949494;">10:18:08</span> 1 DISK genta Escherich… human 18 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> 2025-09-10 <span style="color: #949494;">14:27:37</span> 1 MIC amoxicillin Escherich… human 8 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> 2025-09-10 <span style="color: #949494;">14:27:37</span> 1 MIC cipro Escherich… human 0.256 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> 2025-09-10 <span style="color: #949494;">14:27:38</span> 1 DISK tobra Escherich… human 16 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> 2025-09-10 <span style="color: #949494;">14:27:38</span> 1 DISK genta Escherich… human 18 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 11 more variables: ab &lt;ab&gt;, mo &lt;mo&gt;, host &lt;chr&gt;, input &lt;chr&gt;,</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># outcome &lt;sir&gt;, notes &lt;chr&gt;, guideline &lt;chr&gt;, ref_table &lt;chr&gt;, uti &lt;lgl&gt;,</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># breakpoint_S_R &lt;chr&gt;, site &lt;chr&gt;</span></span>
@@ -619,7 +619,7 @@ Breakpoints are currently implemented from EUCAST 2011-2025 and CLSI 2011-2025,
<span class="r-in"><span><span class="co"># For CLEANING existing SIR values -------------------------------------</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="fu">as.sir</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="st">"S"</span>, <span class="st">"SDD"</span>, <span class="st">"I"</span>, <span class="st">"R"</span>, <span class="st">"NI"</span>, <span class="st">"A"</span>, <span class="st">"B"</span>, <span class="st">"C"</span><span class="op">)</span><span class="op">)</span></span></span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>in <span style="background-color: #EEEEEE;">`as.sir()`</span>: 3 results in index '21' truncated (38%) that were invalid</span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>in <span style="background-color: #EEEEEE;">`as.sir()`</span>: 3 results in index '20' truncated (38%) that were invalid</span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> antimicrobial interpretations: "A", "B", and "C"</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Class 'sir'</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] S SDD I R NI &lt;NA&gt; &lt;NA&gt; &lt;NA&gt;</span>

2
reference/atc_online.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/av_from_text.html
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@@ -7,7 +7,7 @@
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reference/av_property.html
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@@ -7,7 +7,7 @@
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reference/availability.html
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@@ -7,7 +7,7 @@
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reference/bug_drug_combinations.html
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@@ -7,7 +7,7 @@
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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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reference/count.html
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@@ -9,7 +9,7 @@ count_resistant() should be used to count resistant isolates, count_susceptible(
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@@ -7,7 +7,7 @@
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reference/esbl_isolates.html
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@@ -1,112 +0,0 @@
<!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>Data Set with 500 ESBL Isolates — esbl_isolates • 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="Data Set with 500 ESBL Isolates — esbl_isolates"><meta name="description" content="A data set containing 500 microbial isolates with MIC values of common antibiotics and a binary esbl column for extended-spectrum beta-lactamase (ESBL) production. This data set contains randomised fictitious data but reflects reality and can be used to practise AMR-related machine learning, e.g., classification modelling with tidymodels."><meta property="og:description" content="A data set containing 500 microbial isolates with MIC values of common antibiotics and a binary esbl column for extended-spectrum beta-lactamase (ESBL) production. This data set contains randomised fictitious data but reflects reality and can be used to practise AMR-related machine learning, e.g., classification modelling with tidymodels."><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>
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<main id="main" class="col-md-9"><div class="page-header">
<img src="../logo.svg" class="logo" alt=""><h1>Data Set with 500 ESBL Isolates</h1>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/data.R" class="external-link"><code>R/data.R</code></a></small>
<div class="d-none name"><code>esbl_isolates.Rd</code></div>
</div>
<div class="ref-description section level2">
<p>A data set containing 500 microbial isolates with MIC values of common antibiotics and a binary <code>esbl</code> column for extended-spectrum beta-lactamase (ESBL) production. This data set contains randomised fictitious data but reflects reality and can be used to practise AMR-related machine learning, e.g., classification modelling with <a href="https://amr-for-r.org/articles/AMR_with_tidymodels.html">tidymodels</a>.</p>
</div>
<div class="section level2">
<h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
<div class="sourceCode"><pre class="sourceCode r"><code><span><span class="va">esbl_isolates</span></span></code></pre></div>
</div>
<div class="section level2">
<h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2>
<p>A <a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a> with 500 observations and 19 variables:</p><ul><li><p><code>esbl</code><br> Logical indicator if the isolate is ESBL-producing</p></li>
<li><p><code>genus</code><br> Genus of the microorganism</p></li>
<li><p><code>AMC:COL</code><br> MIC values for 17 antimicrobial agents, transformed to class <code><a href="as.mic.html">mic</a></code> (see <code><a href="as.mic.html">as.mic()</a></code>)</p></li>
</ul></div>
<div class="section level2">
<h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
<p>See our <a href="amr-tidymodels.html">tidymodels integration</a> for an example using this data set.</p>
</div>
<div class="section level2">
<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">esbl_isolates</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 500 × 19</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> esbl genus AMC AMP TZP CXM FOX CTX CAZ GEN TOB TMP SXT</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> FALSE Esch… 32 32 4 64 64 8<span style="color: #BBBBBB;">.00</span> 8<span style="color: #BBBBBB;">.00</span> 1 1 16<span style="color: #BBBBBB;">.0</span> 20</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> FALSE Esch… 32 32 4 64 64 4<span style="color: #BBBBBB;">.00</span> 8<span style="color: #BBBBBB;">.00</span> 1 1 16<span style="color: #BBBBBB;">.0</span> 320</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> FALSE Esch… 4 2 64 8 4 8<span style="color: #BBBBBB;">.00</span> 0.12 16 16 0.5 20</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> FALSE Kleb… 32 32 16 64 64 8<span style="color: #BBBBBB;">.00</span> 8<span style="color: #BBBBBB;">.00</span> 1 1 0.5 20</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> FALSE Esch… 32 32 4 4 4 0.25 2<span style="color: #BBBBBB;">.00</span> 1 1 16<span style="color: #BBBBBB;">.0</span> 320</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> FALSE Citr… 32 32 16 64 64 64<span style="color: #BBBBBB;">.00</span> 32<span style="color: #BBBBBB;">.00</span> 1 1 0.5 20</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> FALSE Morg… 32 32 4 64 64 16<span style="color: #BBBBBB;">.00</span> 2<span style="color: #BBBBBB;">.00</span> 1 1 0.5 20</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> FALSE Prot… 16 32 4 1 4 8<span style="color: #BBBBBB;">.00</span> 0.12 1 1 16<span style="color: #BBBBBB;">.0</span> 320</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> FALSE Ente… 32 32 8 64 64 32<span style="color: #BBBBBB;">.00</span> 4<span style="color: #BBBBBB;">.00</span> 1 1 0.5 20</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> FALSE Citr… 32 32 32 64 64 8<span style="color: #BBBBBB;">.00</span> 64<span style="color: #BBBBBB;">.00</span> 1 1 16<span style="color: #BBBBBB;">.0</span> 320</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 490 more rows</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 6 more variables: NIT &lt;mic&gt;, FOS &lt;mic&gt;, CIP &lt;mic&gt;, IPM &lt;mic&gt;, MEM &lt;mic&gt;,</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># COL &lt;mic&gt;</span></span>
</code></pre></div>
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@@ -9,7 +9,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
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@@ -154,28 +154,28 @@
<span class="r-in"><span><span class="va">df</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/sample.html" class="external-link">sample</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq_len</a></span><span class="op">(</span><span class="fl">2000</span><span class="op">)</span>, size <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>, <span class="op">]</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="fu">get_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">60</span><span class="op">)</span> <span class="co"># indices</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 43 9 7 14 28 40 49 29 19 27 10 44 18 22 42 12 8 36 13 3 46 5 4 35 38</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [26] 16 22 23 16 10 42 13 2 45 18 19 39 32 22 36 40 45 39 40 11 23 25 39 26 23</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [51] 25 12 17 23 30 30 34 16 21 37 40 26 11 7 4 16 43 22 47 37 39 31 25 41 1</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [76] 45 39 23 32 45 20 22 15 14 13 43 9 38 29 6 48 24 21 23 44 19 31 1 3 33</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 17 19 32 7 48 16 36 11 41 30 43 42 3 37 6 42 16 46 12 6 38 15 31 23 44</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [26] 35 42 21 10 21 18 22 9 29 40 8 22 14 31 47 18 26 28 18 25 20 11 49 8 27</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [51] 50 23 46 3 27 6 31 1 33 10 23 31 11 20 46 13 4 24 4 27 8 48 16 2 20</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [76] 35 31 19 33 34 16 14 33 17 46 24 15 17 7 9 39 14 50 5 12 2 45 35 8 28</span>
<span class="r-in"><span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">60</span><span class="op">)</span> <span class="co"># TRUE/FALSE</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [13] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [25] TRUE TRUE FALSE TRUE FALSE FALSE FALSE FALSE TRUE TRUE FALSE FALSE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [37] TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE TRUE FALSE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [49] TRUE FALSE FALSE FALSE TRUE FALSE TRUE FALSE TRUE FALSE TRUE TRUE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [61] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [73] FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE TRUE FALSE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [85] FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE FALSE FALSE FALSE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [97] FALSE FALSE FALSE TRUE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [13] TRUE TRUE TRUE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [25] TRUE TRUE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [37] FALSE TRUE FALSE TRUE FALSE TRUE TRUE FALSE TRUE TRUE FALSE TRUE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [49] FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [61] FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE FALSE FALSE FALSE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [73] FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [85] FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE FALSE FALSE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [97] TRUE FALSE FALSE FALSE</span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># filter on results from the third 60-day episode only, using base R</span></span></span>
<span class="r-in"><span><span class="va">df</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html" class="external-link">which</a></span><span class="op">(</span><span class="fu">get_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, <span class="fl">60</span><span class="op">)</span> <span class="op">==</span> <span class="fl">3</span><span class="op">)</span>, <span class="op">]</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 2 × 46</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> date patient age gender ward mo PEN OXA FLC AMX </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <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 class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> 2002-11-04 304347 62 M Clinical <span style="color: #949494;">B_</span>STRPT<span style="color: #949494;">_</span>PNMN <span style="color: #080808; background-color: #5FD7AF;"> S </span> <span style="color: #B2B2B2;"> NA</span> <span style="color: #B2B2B2;"> NA</span> <span style="color: #080808; background-color: #5FD7AF;"> S </span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> 2002-10-18 E55128 57 F ICU <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 class="r-out co"><span class="r-pr">#&gt;</span> date patient age gender ward mo PEN OXA FLC AMX </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <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 class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> 2002-07-23 F35553 51 M ICU <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 class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> 2002-07-23 F35553 51 M ICU <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 class="r-out co"><span class="r-pr">#&gt;</span> <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 class="r-out co"><span class="r-pr">#&gt;</span> <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 class="r-out co"><span class="r-pr">#&gt;</span> <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>
@@ -209,19 +209,19 @@
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html" class="external-link">arrange</a></span><span class="op">(</span><span class="va">patient</span>, <span class="va">condition</span>, <span class="va">date</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 100 × 4</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Groups: patient, condition [96]</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Groups: patient, condition [95]</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> patient date condition new_episode</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <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;lgl&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 022060 2004-05-04 A TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 060287 2007-03-11 A TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 0E2483 2007-04-06 C TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 101305 2006-12-13 A TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 141061 2014-10-22 A TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 146F70 2009-08-14 A TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 15D386 2004-08-01 B TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 187841 2008-04-22 C TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 195736 2008-08-29 C TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 195736 2008-08-29 C FALSE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 011307 2011-09-20 B TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 011307 2011-09-20 C TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 021368 2016-03-25 A TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 060287 2007-03-11 B TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 078381 2014-07-17 A TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 097186 2015-10-28 B TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 0DBB93 2003-10-02 A TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 0DBF93 2015-12-03 C TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 114570 2003-04-22 A TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 141061 2014-10-22 C TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 90 more rows</span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
@@ -235,19 +235,19 @@
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html" class="external-link">arrange</a></span><span class="op">(</span><span class="va">patient</span>, <span class="va">ward</span>, <span class="va">date</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 100 × 5</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Groups: ward, patient [91]</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> ward date patient new_index new_logical</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <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;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> ICU 2004-05-04 022060 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> Clinical 2007-03-11 060287 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> Clinical 2007-04-06 0E2483 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> Clinical 2006-12-13 101305 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> Clinical 2014-10-22 141061 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> Clinical 2009-08-14 146F70 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> ICU 2004-08-01 15D386 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> Clinical 2008-04-22 187841 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> Clinical 2008-08-29 195736 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> Clinical 2008-08-29 195736 1 FALSE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Groups: ward, patient [93]</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> ward date patient new_index new_logical</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <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;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> Clinical 2011-09-20 011307 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> Clinical 2011-09-20 011307 1 FALSE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> Outpatient 2016-03-25 021368 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> Clinical 2007-03-11 060287 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> ICU 2014-07-17 078381 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> Clinical 2015-10-28 097186 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> ICU 2003-10-02 0DBB93 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> ICU 2015-12-03 0DBF93 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> ICU 2003-04-22 114570 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> Clinical 2014-10-22 141061 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 90 more rows</span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
@@ -263,9 +263,9 @@
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 5</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> ward n_patients n_episodes_365 n_episodes_60 n_episodes_30</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&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 style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Clinical 58 14 38 44</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> ICU 26 7 20 23</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> Outpatient 7 4 6 7</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Clinical 51 12 33 43</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> ICU 31 11 26 30</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> Outpatient 11 8 11 11</span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># grouping on patients and microorganisms leads to the same</span></span></span>
<span class="r-in"><span><span class="co"># results as first_isolate() when using 'episode-based':</span></span></span>
@@ -283,7 +283,7 @@
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/identical.html" class="external-link">identical</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">y</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] FALSE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE</span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># but is_new_episode() has a lot more flexibility than first_isolate(),</span></span></span>
<span class="r-in"><span><span class="co"># since you can now group on anything that seems relevant:</span></span></span>
@@ -294,19 +294,19 @@
<span class="r-in"><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="fu"><a href="https://dplyr.tidyverse.org/reference/group_data.html" class="external-link">group_vars</a></span><span class="op">(</span><span class="va">.</span><span class="op">)</span>, <span class="va">flag_episode</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 100 × 4</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Groups: patient, mo, ward [96]</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> patient mo ward flag_episode</span>
<span class="r-out co"><span class="r-pr">#&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;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 917895 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>CPTS ICU TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 022060 <span style="color: #949494;">B_</span>ENTRBC<span style="color: #949494;">_</span>CLOC ICU TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> C36883 <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 5DF436 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>AURS ICU TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 971739 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>CONS Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 488175 <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 5DB1C8 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>CPTS Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> BC9909 <span style="color: #949494;">B_</span>ENTRBC<span style="color: #949494;">_</span>CLOC Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 5B78D5 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>AURS Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 284FFF <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>EPDR Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Groups: patient, mo, ward [95]</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> patient mo ward flag_episode</span>
<span class="r-out co"><span class="r-pr">#&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;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 690B42 <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI ICU TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 550406 <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI Outpatient TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> F86227 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>CONS Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 859863 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>EPDR ICU TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 987C84 <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> E19440 <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI ICU TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> F42C5F <span style="color: #949494;">B_</span>MRGNL<span style="color: #949494;">_</span>MRGN Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> F54261 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>AURS Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 5D1690 <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI Outpatient TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 874171 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>CONS Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 90 more rows</span></span>
<span class="r-in"><span><span class="co"># }</span></span></span>
</code></pre></div>

2
reference/ggplot_pca.html
View File

@@ -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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

2
reference/ggplot_sir.html
View File

@@ -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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

2
reference/guess_ab_col.html
View File

@@ -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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

8
reference/index.html
View File

@@ -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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">
@@ -388,12 +388,6 @@
<dd>Data Set with 2 000 Example Isolates</dd>
</dl><dl><dt>
<code><a href="esbl_isolates.html">esbl_isolates</a></code>
</dt>
<dd>Data Set with 500 ESBL Isolates</dd>
</dl><dl><dt>
<code><a href="microorganisms.codes.html">microorganisms.codes</a></code>
</dt>

2
reference/intrinsic_resistant.html
View File

@@ -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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

2
reference/italicise_taxonomy.html
View File

@@ -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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

2
reference/join.html
View File

@@ -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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

2
reference/key_antimicrobials.html
View File

@@ -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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

6
reference/kurtosis.html
View File

@@ -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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">
@@ -91,9 +91,9 @@
<div class="section level2">
<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu">kurtosis</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">10000</span><span class="op">)</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 3.069947</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 3.071712</span>
<span class="r-in"><span><span class="fu">kurtosis</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">10000</span><span class="op">)</span>, excess <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] -0.02599697</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] -0.02774835</span>
</code></pre></div>
</div>
</main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>

4
reference/like.html
View File

@@ -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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">
@@ -107,8 +107,6 @@
<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># data.table has a more limited version of %like%, so unload it:</span></span></span>
<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/try.html" class="external-link">try</a></span><span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/detach.html" class="external-link">detach</a></span><span class="op">(</span><span class="st">"package:data.table"</span>, unload <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>, silent <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>‘data.table’ namespace cannot be unloaded:</span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> namespace ‘data.table’ is imported by ‘prodlim’ so cannot be unloaded</span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="va">a</span> <span class="op">&lt;-</span> <span class="st">"This is a test"</span></span></span>
<span class="r-in"><span><span class="va">b</span> <span class="op">&lt;-</span> <span class="st">"TEST"</span></span></span>

2
reference/mdro.html
View File

@@ -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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

88
reference/mean_amr_distance.html
View File

@@ -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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">
@@ -110,30 +110,30 @@
<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">sir</span> <span class="op">&lt;-</span> <span class="fu"><a href="random.html">random_sir</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">sir</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Class 'sir'</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] R R I R I I S R S I</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] I I R I R S S S I S</span>
<span class="r-in"><span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">sir</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 1.1618950 1.1618950 -0.7745967 1.1618950 -0.7745967 -0.7745967</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [7] -0.7745967 1.1618950 -0.7745967 -0.7745967</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] -0.4743416 -0.4743416 1.8973666 -0.4743416 1.8973666 -0.4743416</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [7] -0.4743416 -0.4743416 -0.4743416 -0.4743416</span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="va">mic</span> <span class="op">&lt;-</span> <span class="fu"><a href="random.html">random_mic</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">mic</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Class 'mic'</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.032 0.5 1 &gt;=8 4 0.016 &gt;=8 1 0.004 0.008</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.004 2 0.002 0.0001 0.004 0.002 &gt;=4 0.0002 0.032 0.004 </span>
<span class="r-in"><span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">mic</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] -0.7311752 0.2104422 0.4478776 1.1601837 0.9227483 -0.9686106</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [7] 1.1601837 0.4478776 -1.4434813 -1.2060459</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] -0.2047915 1.5799751 -0.4038557 -1.2641969 -0.2047915 -0.4038557</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [7] 1.7790393 -1.0651327 0.3924011 -0.2047915</span>
<span class="r-in"><span><span class="co"># equal to the Z-score of their log2:</span></span></span>
<span class="r-in"><span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log2</a></span><span class="op">(</span><span class="va">mic</span><span class="op">)</span> <span class="op">-</span> <span class="fu"><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log2</a></span><span class="op">(</span><span class="va">mic</span><span class="op">)</span><span class="op">)</span><span class="op">)</span> <span class="op">/</span> <span class="fu"><a href="https://rdrr.io/r/stats/sd.html" class="external-link">sd</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log2</a></span><span class="op">(</span><span class="va">mic</span><span class="op">)</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] -0.7311752 0.2104422 0.4478776 1.1601837 0.9227483 -0.9686106</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [7] 1.1601837 0.4478776 -1.4434813 -1.2060459</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] -0.2047915 1.5799751 -0.4038557 -1.2641969 -0.2047915 -0.4038557</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [7] 1.7790393 -1.0651327 0.3924011 -0.2047915</span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="va">disk</span> <span class="op">&lt;-</span> <span class="fu"><a href="random.html">random_disk</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">disk</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Class 'disk'</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 50 49 38 33 31 17 42 43 46 37</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 43 12 28 32 22 31 35 25 43 35</span>
<span class="r-in"><span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">disk</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 1.15131286 1.05032051 -0.06059541 -0.56555720 -0.76754191 -2.18143490</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [7] 0.34337401 0.44436637 0.74734344 -0.16158777</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 1.30998909 -1.96498364 -0.27467513 0.14790199 -0.90854082 0.04225771</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [7] 0.46483484 -0.59160798 1.30998909 0.46483484</span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="va">y</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>
<span class="r-in"><span> id <span class="op">=</span> <span class="va">LETTERS</span><span class="op">[</span><span class="fl">1</span><span class="op">:</span><span class="fl">10</span><span class="op">]</span>,</span></span>
@@ -144,35 +144,35 @@
<span class="r-in"><span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">y</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> id amox cipr gent tobr</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1 A I 27 &gt;=2 8</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 B S 28 1 8</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 C R 33 1 8</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 D R 32 1 16</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 E I 25 0.5 16</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 F I 19 0.5 8</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 G S 23 0.5 16</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 H R 27 0.5 8</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 I S 29 1 8</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 J R 32 0.5 16</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1 A S 31 2 &gt;=16</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 B S 27 &lt;=1 8</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 C R 25 2 4</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 D R 25 &lt;=1 2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 E I 31 &lt;=1 2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 F S 32 &lt;=1 8</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 G I 29 2 2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 H S 18 &lt;=1 4</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 I S 28 &lt;=1 4</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 J R 17 &lt;=1 2</span>
<span class="r-in"><span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">y</span><span class="op">)</span></span></span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #0000BB;">ℹ Calculating mean AMR distance based on columns "amox", "cipr", "gent",</span></span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #0000BB;"> and "tobr"</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.08471751 -0.21572693 0.55391610 0.98093500 -0.26046456 -1.08721162</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [7] -0.37467261 -0.14625651 -0.15862291 0.62338653</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.90606144 -0.03989270 0.66241774 -0.09230226 -0.32300020 0.19914999</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [7] 0.09893189 -0.70734036 -0.22925499 -0.47477055</span>
<span class="r-in"><span><span class="va">y</span><span class="op">$</span><span class="va">amr_distance</span> <span class="op">&lt;-</span> <span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">y</span>, <span class="fu"><a href="as.mic.html">is.mic</a></span><span class="op">(</span><span class="va">y</span><span class="op">)</span><span class="op">)</span></span></span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #0000BB;">ℹ Calculating mean AMR distance based on columns "gent" and "tobr"</span></span>
<span class="r-in"><span><span class="va">y</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/order.html" class="external-link">order</a></span><span class="op">(</span><span class="va">y</span><span class="op">$</span><span class="va">amr_distance</span><span class="op">)</span>, <span class="op">]</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> id amox cipr gent tobr amr_distance</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 F I 19 0.5 8 -0.8163565</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 H R 27 0.5 8 -0.8163565</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 B S 28 1 8 -0.1012596</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 C R 33 1 8 -0.1012596</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 I S 29 1 8 -0.1012596</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 E I 25 0.5 16 0.1518893</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 G S 23 0.5 16 0.1518893</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 J R 32 0.5 16 0.1518893</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1 A I 27 &gt;=2 8 0.6138374</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 D R 32 1 16 0.8669863</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 D R 25 &lt;=1 2 -0.7848712</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 E I 31 &lt;=1 2 -0.7848712</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 J R 17 &lt;=1 2 -0.7848712</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 H S 18 &lt;=1 4 -0.3105295</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 I S 28 &lt;=1 4 -0.3105295</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 B S 27 &lt;=1 8 0.1638121</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 F S 32 &lt;=1 8 0.1638121</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 G I 29 2 2 0.2502272</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 C R 25 2 4 0.7245688</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1 A S 31 2 &gt;=16 1.6732521</span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
<span class="r-in"><span> <span class="va">y</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
@@ -185,16 +185,16 @@
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #0000BB;">ℹ Calculating mean AMR distance based on columns "amox", "cipr", "gent",</span></span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #0000BB;"> and "tobr"</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> id amox cipr gent tobr amr_distance check_id_C</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1 C R 33 1 8 0.55391610 0.00000000</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 J R 32 0.5 16 0.62338653 0.06947042</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 D R 32 1 16 0.98093500 0.42701889</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 A I 27 &gt;=2 8 0.08471751 0.46919859</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 H R 27 0.5 8 -0.14625651 0.70017262</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 I S 29 1 8 -0.15862291 0.71253901</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 B S 28 1 8 -0.21572693 0.76964304</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 E I 25 0.5 16 -0.26046456 0.81438066</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 G S 23 0.5 16 -0.37467261 0.92858871</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 F I 19 0.5 8 -1.08721162 1.64112773</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1 C R 25 2 4 0.66241774 0.0000000</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 A S 31 2 &gt;=16 0.90606144 0.2436437</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 F S 32 &lt;=1 8 0.19914999 0.4632678</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 G I 29 2 2 0.09893189 0.5634858</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 B S 27 &lt;=1 8 -0.03989270 0.7023104</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 D R 25 &lt;=1 2 -0.09230226 0.7547200</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 I S 28 &lt;=1 4 -0.22925499 0.8916727</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 E I 31 &lt;=1 2 -0.32300020 0.9854179</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 J R 17 &lt;=1 2 -0.47477055 1.1371883</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 H S 18 &lt;=1 4 -0.70734036 1.3697581</span>
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
<span class="r-in"><span> <span class="co"># support for groups</span></span></span>
<span class="r-in"><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>

2
reference/microorganisms.codes.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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

2
reference/microorganisms.groups.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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

2
reference/microorganisms.html
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@@ -9,7 +9,7 @@ This data set is carefully crafted, yet made 100% reproducible from public and a
<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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

2
reference/mo_matching_score.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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

2
reference/mo_property.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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

2
reference/mo_source.html
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@@ -9,7 +9,7 @@ This is the fastest way to have your organisation (or analysis) specific codes p
<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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

2
reference/pca.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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

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reference/plot.html
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@@ -9,7 +9,7 @@ Especially the scale_*_mic() functions are relevant wrappers to plot MIC values
<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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

2
reference/proportion.html
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@@ -9,7 +9,7 @@ resistance() should be used to calculate resistance, susceptibility() should be
<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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">

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34
reference/random.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="">3.0.0.9021</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.0.9029</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">
@@ -111,15 +111,15 @@
<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu">random_mic</span><span class="op">(</span><span class="fl">25</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Class 'mic'</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 1 0.064 2 0.016 128 0.001 0.004 0.008 64 0.064 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [11] 0.002 0.001 0.016 0.004 0.0005 0.0005 0.125 0.032 0.032 8 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [21] 2 8 0.008 0.0005 8 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.016 0.125 0.125 0.25 0.5 0.004 0.002 0.002 0.032 0.004 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [11] 0.032 0.0005 0.5 1 0.016 0.008 2 0.125 0.25 0.25 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [21] 0.032 1 0.008 0.004 0.25 </span>
<span class="r-in"><span><span class="fu">random_disk</span><span class="op">(</span><span class="fl">25</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Class 'disk'</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 46 38 45 47 24 28 45 43 19 23 44 19 31 22 40 39 39 36 35 14 34 45 21 19 39</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 47 20 36 18 44 43 25 28 26 44 36 42 8 28 44 31 29 49 30 28 39 49 25 49 48</span>
<span class="r-in"><span><span class="fu">random_sir</span><span class="op">(</span><span class="fl">25</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Class 'sir'</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] I S R I R I S S S R R R I I R R I S R R S I S R I</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] R S R S R R S I I I S R R S I I S I I I S S R S S</span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># add more skewedness, make more realistic by setting a bug and/or drug:</span></span></span>
<span class="r-in"><span><span class="va">disks</span> <span class="op">&lt;-</span> <span class="fu">random_disk</span><span class="op">(</span><span class="fl">100</span>, severity <span class="op">=</span> <span class="fl">2</span>, mo <span class="op">=</span> <span class="st">"Escherichia coli"</span>, ab <span class="op">=</span> <span class="st">"CIP"</span><span class="op">)</span></span></span>
@@ -132,28 +132,28 @@
<span class="r-in"><span><span class="co"># \donttest{</span></span></span>
<span class="r-in"><span><span class="fu">random_mic</span><span class="op">(</span><span class="fl">25</span>, <span class="st">"Klebsiella pneumoniae"</span><span class="op">)</span> <span class="co"># range 0.0625-64</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Class 'mic'</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 2 0.032 32 0.5 0.001 0.008 0.002 4 0.0005 1 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [11] 0.001 1 8 0.002 0.25 2 0.016 0.004 0.25 0.125 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [21] 0.002 0.5 0.004 &gt;=256 0.0005</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.004 4 0.032 16 0.016 16 0.001 0.0002 0.002 0.004 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [11] 0.001 0.0005 0.0001 0.002 0.125 &gt;=64 0.004 0.0005 0.001 0.0002</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [21] 0.0005 0.001 0.0005 0.004 0.032 </span>
<span class="r-in"><span><span class="fu">random_mic</span><span class="op">(</span><span class="fl">25</span>, <span class="st">"Klebsiella pneumoniae"</span>, <span class="st">"meropenem"</span><span class="op">)</span> <span class="co"># range 0.0625-16</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Class 'mic'</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 4 &gt;=8 4 &gt;=8 4 &gt;=8 4 4 4 4 4 4 &gt;=8 &gt;=8 4 &gt;=8 4 4 4 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [20] 4 4 4 4 4 4 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] &lt;=0.5 &lt;=0.5 &lt;=0.5 1 &lt;=0.5 &lt;=0.5 &lt;=0.5 &lt;=0.5 &lt;=0.5 &lt;=0.5 1 1 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [13] &lt;=0.5 &lt;=0.5 &lt;=0.5 &lt;=0.5 1 &lt;=0.5 &lt;=0.5 &lt;=0.5 &lt;=0.5 1 1 &lt;=0.5</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [25] &lt;=0.5</span>
<span class="r-in"><span><span class="fu">random_mic</span><span class="op">(</span><span class="fl">25</span>, <span class="st">"Streptococcus pneumoniae"</span>, <span class="st">"meropenem"</span><span class="op">)</span> <span class="co"># range 0.0625-4</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Class 'mic'</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] &lt;=0.25 0.5 &lt;=0.25 &lt;=0.25 &lt;=0.25 0.5 &lt;=0.25 &lt;=0.25 &lt;=0.25 &lt;=0.25</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [11] &lt;=0.25 &lt;=0.25 0.5 &lt;=0.25 &lt;=0.25 &lt;=0.25 0.5 &lt;=0.25 0.5 &lt;=0.25</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [21] &lt;=0.25 0.5 &lt;=0.25 0.5 0.5 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] &gt;=2 1 1 1 &gt;=2 &gt;=2 &gt;=2 1 &gt;=2 1 1 &gt;=2 1 1 1 &gt;=2 1 1 1 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [20] &gt;=2 &gt;=2 1 1 1 1 </span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="fu">random_disk</span><span class="op">(</span><span class="fl">25</span>, <span class="st">"Klebsiella pneumoniae"</span><span class="op">)</span> <span class="co"># range 8-50</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Class 'disk'</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 33 26 16 27 29 33 24 17 17 15 16 26 26 14 17 29 25 25 24 32 32 34 18 31 10</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 28 12 30 26 9 34 30 19 32 31 33 34 30 19 15 24 18 34 12 32 29 33 29 32 17</span>
<span class="r-in"><span><span class="fu">random_disk</span><span class="op">(</span><span class="fl">25</span>, <span class="st">"Klebsiella pneumoniae"</span>, <span class="st">"ampicillin"</span><span class="op">)</span> <span class="co"># range 11-17</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Class 'disk'</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 19 20 11 14 12 12 17 16 12 10 15 22 19 21 19 17 18 19 21 17 21 15 17 12 19</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 18 15 19 13 22 20 22 13 18 14 19 13 12 22 20 21 12 20 18 19 20 22 18 17 20</span>
<span class="r-in"><span><span class="fu">random_disk</span><span class="op">(</span><span class="fl">25</span>, <span class="st">"Streptococcus pneumoniae"</span>, <span class="st">"ampicillin"</span><span class="op">)</span> <span class="co"># range 12-27</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Class 'disk'</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 27 24 31 22 35 28 26 32 24 18 35 33 24 28 33 25 35 25 32 24 26 20 23 22 33</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 21 31 27 28 30 34 16 32 28 25 25 23 29 26 24 28 27 33 30 19 30 22 27 22 32</span>
<span class="r-in"><span><span class="co"># }</span></span></span>
</code></pre></div>
</div>

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