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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="">3.0.1.9063</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9065</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">
@@ -341,7 +341,11 @@ traditional antibiogram remains fit for purpose.</p>
<span><span class="co">#&gt; <span style="color: #949494;"># IPM &lt;sir&gt;, MEM &lt;sir&gt;, MTR &lt;sir&gt;, CHL &lt;sir&gt;, COL &lt;sir&gt;, MUP &lt;sir&gt;, …</span></span></span>
<span></span>
<span><span class="co"># Add a synthetic syndrome column for demonstration</span></span>
<span><span class="va">data</span><span class="op">$</span><span class="va">syndrome</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse</a></span><span class="op">(</span><span class="va">data</span><span class="op">$</span><span class="va">mo</span> <span class="op"><a href="../reference/like.html">%like%</a></span> <span class="st">"coli"</span>, <span class="st">"UTI"</span>, <span class="st">"Non-UTI"</span><span class="op">)</span></span></code></pre></div>
<span><span class="va">data</span><span class="op">$</span><span class="va">syndrome</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse</a></span><span class="op">(</span><span class="va">data</span><span class="op">$</span><span class="va">mo</span> <span class="op"><a href="../reference/like.html">%like%</a></span> <span class="st">"coli"</span>, <span class="st">"UTI"</span>, <span class="st">"Non-UTI"</span><span class="op">)</span></span>
<span></span>
<span><span class="co"># Keep only 10 most common microorganisms</span></span>
<span><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/top_n_microorganisms.html">top_n_microorganisms</a></span><span class="op">(</span><span class="va">data</span>, n <span class="op">=</span> <span class="fl">10</span>, property <span class="op">=</span> <span class="st">"species"</span><span class="op">)</span></span>
<span><span class="co">#&gt; <span style="color: #00BBBB;">ℹ</span> Using column <span style="color: #00BB00; font-weight: bold;">mo</span> as input for `col_mo`.</span></span></code></pre></div>
</div>
<div class="section level3">
<h3 id="basic-wisca">Basic WISCA<a class="anchor" aria-label="anchor" href="#basic-wisca"></a>
@@ -357,9 +361,9 @@ traditional antibiogram remains fit for purpose.</p>
<th align="left">Gentamicin</th>
</tr></thead>
<tbody><tr class="odd">
<td align="left">74.2% (72.1-76.1%)</td>
<td align="left">78.4% (75.6-81.1%)</td>
<td align="left">72.5% (70.4-74.6%)</td>
<td align="left">76.8% (74.7-79.1%)</td>
<td align="left">81.5% (78.9-84.1%)</td>
<td align="left">82.9% (81-84.8%)</td>
</tr></tbody>
</table>
</div>
@@ -385,9 +389,9 @@ covers the pathogen:</p>
<th align="left">Amoxicillin/clavulanic acid + Gentamicin</th>
</tr></thead>
<tbody><tr class="odd">
<td align="left">74.2% (72.2-76.1%)</td>
<td align="left">88.8% (87.2-90.4%)</td>
<td align="left">90.8% (89.4-92.2%)</td>
<td align="left">76.8% (74.6-78.9%)</td>
<td align="left">89.6% (88-91.1%)</td>
<td align="left">93.7% (92.5-94.9%)</td>
</tr></tbody>
</table>
</div>
@@ -397,10 +401,11 @@ covers the pathogen:</p>
<p>Use <code>syndromic_group</code> to produce separate WISCA estimates
per clinical stratum. You can pass a column name or any expression:</p>
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/antibiogram.html">wisca</a></span><span class="op">(</span><span class="va">data</span>,</span>
<code class="sourceCode R"><span><span class="va">wisca_out</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/antibiogram.html">wisca</a></span><span class="op">(</span><span class="va">data</span>,</span>
<span> antimicrobials <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"AMC"</span>, <span class="st">"AMC + CIP"</span>, <span class="st">"AMC + GEN"</span><span class="op">)</span>,</span>
<span> syndromic_group <span class="op">=</span> <span class="st">"syndrome"</span></span>
<span><span class="op">)</span></span></code></pre></div>
<span><span class="op">)</span></span>
<span><span class="va">wisca_out</span></span></code></pre></div>
<table class="table">
<colgroup>
<col width="12%">
@@ -417,15 +422,15 @@ per clinical stratum. You can pass a column name or any expression:</p>
<tbody>
<tr class="odd">
<td align="left">Non-UTI</td>
<td align="left">70.3% (67.9-72.7%)</td>
<td align="left">86.8% (84.9-88.7%)</td>
<td align="left">88.4% (86.4-90.2%)</td>
<td align="left">72.5% (69.9-75.1%)</td>
<td align="left">86.9% (84.8-89%)</td>
<td align="left">91.4% (89.5-93%)</td>
</tr>
<tr class="even">
<td align="left">UTI</td>
<td align="left">80.3% (77-83.3%)</td>
<td align="left">88.4% (85.7-90.8%)</td>
<td align="left">91% (88.3-93.3%)</td>
<td align="left">86% (82.5-89%)</td>
<td align="left">94.8% (92.5-96.6%)</td>
<td align="left">97.9% (96.3-99%)</td>
</tr>
</tbody>
</table>
@@ -453,15 +458,15 @@ all be used for the <code><a href="../reference/antibiogram.html">wisca()</a></c
<tbody>
<tr class="odd">
<td align="left">Non-UCI</td>
<td align="left">70.4% (68-72.8%)</td>
<td align="left">86.7% (84.6-88.7%)</td>
<td align="left">88.5% (86.5-90.2%)</td>
<td align="left">72.6% (69.9-75.3%)</td>
<td align="left">87% (84.9-89.1%)</td>
<td align="left">91.4% (89.7-92.9%)</td>
</tr>
<tr class="even">
<td align="left">UCI</td>
<td align="left">80.3% (77.2-83.5%)</td>
<td align="left">88.4% (85.5-90.8%)</td>
<td align="left">91% (88.4-93.1%)</td>
<td align="left">86% (82.7-89%)</td>
<td align="left">94.8% (92.7-96.4%)</td>
<td align="left">97.9% (96.5-99%)</td>
</tr>
</tbody>
</table>
@@ -482,6 +487,62 @@ preferred on stewardship grounds.</li>
clinically meaningful difference in coverage.</li>
</ul>
</div>
<div class="section level3">
<h3 id="plotting">Plotting<a class="anchor" aria-label="anchor" href="#plotting"></a>
</h3>
<p>WISCA results can be visualised in several ways. All plot functions
work on the output of <code><a href="../reference/antibiogram.html">wisca()</a></code> (or
<code>antibiogram(..., wisca = TRUE)</code>).</p>
<p>Below we use the <code>wisca_out</code> object that was generated
above.</p>
<div class="section level4">
<h4 id="coverage-with-credible-intervals">Coverage with credible intervals<a class="anchor" aria-label="anchor" href="#coverage-with-credible-intervals"></a>
</h4>
<p>The extended <code><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot()</a></code> method from the
<code>ggplot2()</code> package produces a point-and-interval plot
showing the coverage estimate and 95% credible interval for each
regimen, grouped by syndromic stratum. This is the most direct way to
compare regimens: overlapping intervals suggest clinical
non-inferiority, non-overlapping intervals indicate a meaningful
difference.</p>
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span><span class="va">wisca_out</span><span class="op">)</span></span></code></pre></div>
<p><img src="WISCA_files/figure-html/unnamed-chunk-6-1.png" class="r-plt" alt="" width="720"></p>
</div>
<div class="section level4">
<h4 id="susceptibility-vs--incidence-weight">Susceptibility vs. incidence weight<a class="anchor" aria-label="anchor" href="#susceptibility-vs--incidence-weight"></a>
</h4>
<p><code><a href="../reference/antibiogram.html">wisca_plot()</a></code> produces a scatter plot of the Monte Carlo
simulation draws, showing each pathogen’s susceptibility (x-axis)
against its incidence weight (y-axis) for each regimen. Each dot
represents one of 1,000 simulated draws, so the spread reflects
posterior uncertainty. This plot reveals <em>why</em> a regimen achieves
its coverage: you can see which pathogens dominate the syndrome (high on
the y-axis), how susceptible they are (position on the x-axis), and how
uncertain both estimates are (spread of the cloud). The dashed vertical
lines denote the point estimates, i.e., the coverage percentages. The
ribbon behind the dashed lines denote the credible interval, which is
95% at default.</p>
<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/antibiogram.html">wisca_plot</a></span><span class="op">(</span><span class="va">wisca_out</span><span class="op">)</span></span></code></pre></div>
<p><img src="WISCA_files/figure-html/unnamed-chunk-7-1.png" class="r-plt" alt="" width="720"></p>
</div>
<div class="section level4">
<h4 id="posterior-coverage-distributions">Posterior coverage distributions<a class="anchor" aria-label="anchor" href="#posterior-coverage-distributions"></a>
</h4>
<p>Setting <code>wisca_plot_type = "posterior_coverage"</code> shows the
full posterior distribution of coverage for each regimen as a density
curve. This is the most complete representation of what the Bayesian
model produces: each curve shows the relative likelihood of each
coverage value across all 1,000 simulations. Narrow, tall peaks indicate
high certainty; wide, flat curves indicate greater uncertainty. Where
two curves overlap, the regimens cannot be confidently
distinguished.</p>
<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/antibiogram.html">wisca_plot</a></span><span class="op">(</span><span class="va">wisca_out</span>, wisca_plot_type <span class="op">=</span> <span class="st">"posterior_coverage"</span><span class="op">)</span></span></code></pre></div>
<p><img src="WISCA_files/figure-html/unnamed-chunk-8-1.png" class="r-plt" alt="" width="720"></p>
</div>
</div>
</div>
<div class="section level2">
<h2 id="sensible-defaults-which-can-be-customised">Sensible defaults, which can be customised<a class="anchor" aria-label="anchor" href="#sensible-defaults-which-can-be-customised"></a>
@@ -554,7 +615,7 @@ by any clinical variable</li>
intervals that honestly communicate uncertainty</li>
</ul>
<p>It is available in the <code>AMR</code> package via either:</p>
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/antibiogram.html">wisca</a></span><span class="op">(</span><span class="va">...</span><span class="op">)</span></span>
<span></span>
<span><span class="fu"><a href="../reference/antibiogram.html">antibiogram</a></span><span class="op">(</span><span class="va">...</span>, wisca <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
@@ -593,7 +654,7 @@ of weighted-incidence syndromic combination antibiograms (WISCA).
<footer><div class="pkgdown-footer-left">
<p><code>AMR</code> (for R). Free and open-source, licenced under the <a target="_blank" href="https://github.com/msberends/AMR/blob/main/LICENSE" class="external-link">GNU General Public License version 2.0 (GPL-2)</a>.<br>Developed at the <a target="_blank" href="https://www.rug.nl" class="external-link">University of Groningen</a> and <a target="_blank" href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a> in The Netherlands.</p>
<p><code>AMR</code> (for R). Free and open-source, licenced under the <a target="_blank" href="https://github.com/msberends/AMR/blob/main/LICENSE" class="external-link">GNU GPL 2.0</a>. Developed at the <a target="_blank" href="https://www.rug.nl" class="external-link">University of Groningen</a> and <a target="_blank" href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a> in The Netherlands, in collaboration with <a href="https://amr-for-r.org/authors.html">many colleagues from around the world</a>.</p>
</div>
<div class="pkgdown-footer-right">