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<meta property="og:description" content="These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in dplyrs summarise and support grouped variables, see Examples.
count_R and count_IR can be used to count resistant isolates, count_S and count_SI can be used to count susceptible isolates." />
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<h1>Count isolates</h1>
<div class="hidden name"><code>count.Rd</code></div>
</div>
<div class="ref-description">
<p>These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in <code>dplyr</code>s <code><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></code> and support grouped variables, see <em>Examples</em>.</p>
<p><code>count_R</code> and <code>count_IR</code> can be used to count resistant isolates, <code>count_S</code> and <code>count_SI</code> can be used to count susceptible isolates.<br /></p>
</div>
<pre class="usage"><span class='fu'>count_R</span>(<span class='no'>...</span>, <span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>count_IR</span>(<span class='no'>...</span>, <span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>count_I</span>(<span class='no'>...</span>, <span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>count_SI</span>(<span class='no'>...</span>, <span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>count_S</span>(<span class='no'>...</span>, <span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>count_all</span>(<span class='no'>...</span>)
<span class='fu'>n_rsi</span>(<span class='no'>...</span>)
<span class='fu'>count_df</span>(<span class='no'>data</span>, <span class='kw'>translate_ab</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a></span>(<span class='st'>"get_antibiotic_names"</span>,
<span class='st'>"official"</span>), <span class='kw'>combine_IR</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>...</th>
<td><p>one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with <code><a href='as.rsi.html'>as.rsi</a></code> if needed.</p></td>
</tr>
<tr>
<th>also_single_tested</th>
<td><p>a logical to indicate whether (in combination therapies) also observations should be included where not all antibiotics were tested, but at least one of the tested antibiotics contains a target interpretation (e.g. S in case of <code>portion_S</code> and R in case of <code>portion_R</code>). <strong>This would lead to selection bias in almost all cases.</strong></p></td>
</tr>
<tr>
<th>data</th>
<td><p>a <code>data.frame</code> containing columns with class <code>rsi</code> (see <code><a href='as.rsi.html'>as.rsi</a></code>)</p></td>
</tr>
<tr>
<th>translate_ab</th>
<td><p>a column name of the <code><a href='antibiotics.html'>antibiotics</a></code> data set to translate the antibiotic abbreviations to, using <code><a href='abname.html'>abname</a></code>. This can be set with <code><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a>("get_antibiotic_names")</code>.</p></td>
</tr>
<tr>
<th>combine_IR</th>
<td><p>a logical to indicate whether all values of I and R must be merged into one, so the output only consists of S vs. IR (susceptible vs. non-susceptible)</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p>Wickham H. <strong>Tidy Data.</strong> The Journal of Statistical Software, vol. 59, 2014. <a href='http://vita.had.co.nz/papers/tidy-data.html'>http://vita.had.co.nz/papers/tidy-data.html</a></p>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Integer</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>These functions are meant to count isolates. Use the <code><a href='portion.html'>portion</a>_*</code> functions to calculate microbial resistance.</p>
<p><code>n_rsi</code> is an alias of <code>count_all</code>. They can be used to count all available isolates, i.e. where all input antibiotics have an available result (S, I or R). Their use is equal to <code><a href='https://dplyr.tidyverse.org/reference/n_distinct.html'>n_distinct</a></code>. Their function is equal to <code>count_S(...) + count_IR(...)</code>.</p>
<p><code>count_df</code> takes any variable from <code>data</code> that has an <code>"rsi"</code> class (created with <code><a href='as.rsi.html'>as.rsi</a></code>) and counts the amounts of R, I and S. The resulting <em>tidy data</em> (see Source) <code>data.frame</code> will have three rows (S/I/R) and a column for each variable with class <code>"rsi"</code>.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a comprehensive tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='portion.html'>portion</a>_*</code> to calculate microbial resistance and susceptibility.</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='co'># septic_patients is a data set available in the AMR package. It is true, genuine data.</span>
?<span class='no'>septic_patients</span>
<span class='co'># Count resistant isolates</span>
<span class='fu'>count_R</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)
<span class='fu'>count_IR</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)
<span class='co'># Or susceptible isolates</span>
<span class='fu'>count_S</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)
<span class='fu'>count_SI</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)
<span class='co'># Count all available isolates</span>
<span class='fu'>count_all</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)
<span class='fu'>n_rsi</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)
<span class='co'># Since n_rsi counts available isolates, you can</span>
<span class='co'># calculate back to count e.g. non-susceptible isolates.</span>
<span class='co'># This results in the same:</span>
<span class='fu'>count_IR</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)
<span class='fu'><a href='portion.html'>portion_IR</a></span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>) * <span class='fu'>n_rsi</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(<span class='kw'>R</span> <span class='kw'>=</span> <span class='fu'>count_R</span>(<span class='no'>cipr</span>),
<span class='kw'>I</span> <span class='kw'>=</span> <span class='fu'>count_I</span>(<span class='no'>cipr</span>),
<span class='kw'>S</span> <span class='kw'>=</span> <span class='fu'>count_S</span>(<span class='no'>cipr</span>),
<span class='kw'>n1</span> <span class='kw'>=</span> <span class='fu'>count_all</span>(<span class='no'>cipr</span>), <span class='co'># the actual total; sum of all three</span>
<span class='kw'>n2</span> <span class='kw'>=</span> <span class='fu'>n_rsi</span>(<span class='no'>cipr</span>), <span class='co'># same - analogous to n_distinct</span>
<span class='kw'>total</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/n.html'>n</a></span>()) <span class='co'># NOT the number of tested isolates!</span>
<span class='co'># Count co-resistance between amoxicillin/clav acid and gentamicin,</span>
<span class='co'># so we can see that combination therapy does a lot more than mono therapy.</span>
<span class='co'># Please mind that `portion_S` calculates percentages right away instead.</span>
<span class='fu'>count_S</span>(<span class='no'>septic_patients</span>$<span class='no'>amcl</span>) <span class='co'># S = 1342 (71.4%)</span>
<span class='fu'>count_all</span>(<span class='no'>septic_patients</span>$<span class='no'>amcl</span>) <span class='co'># n = 1879</span>
<span class='fu'>count_S</span>(<span class='no'>septic_patients</span>$<span class='no'>gent</span>) <span class='co'># S = 1372 (74.0%)</span>
<span class='fu'>count_all</span>(<span class='no'>septic_patients</span>$<span class='no'>gent</span>) <span class='co'># n = 1855</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/with'>with</a></span>(<span class='no'>septic_patients</span>,
<span class='fu'>count_S</span>(<span class='no'>amcl</span>, <span class='no'>gent</span>)) <span class='co'># S = 1660 (92.3%)</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/with'>with</a></span>(<span class='no'>septic_patients</span>, <span class='co'># n = 1798</span>
<span class='fu'>n_rsi</span>(<span class='no'>amcl</span>, <span class='no'>gent</span>))
<span class='co'># Get portions S/I/R immediately of all rsi columns</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>amox</span>, <span class='no'>cipr</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>count_df</span>(<span class='kw'>translate</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='co'># It also supports grouping variables</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>hospital_id</span>, <span class='no'>amox</span>, <span class='no'>cipr</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>count_df</span>(<span class='kw'>translate</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='co'># }</span></pre>
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<h2>Contents</h2>
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<li><a href="#arguments">Arguments</a></li>
<li><a href="#source">Source</a></li>
<li><a href="#value">Value</a></li>
<li><a href="#details">Details</a></li>
<li><a href="#read-more-on-our-website-">Read more on our website!</a></li>
<li><a href="#see-also">See also</a></li>
<li><a href="#examples">Examples</a></li>
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