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@ -41,7 +41,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9030</span>
</span>
</div>
@ -187,7 +187,7 @@
<h1>How to conduct AMR analysis</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">10 November 2019</h4>
<h4 class="date">11 November 2019</h4>
<div class="hidden name"><code>AMR.Rmd</code></div>
@ -196,7 +196,7 @@
<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">R Markdown</a>. However, the methodology remains unchanged. This page was generated on 10 November 2019.</p>
<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">R Markdown</a>. However, the methodology remains unchanged. This page was generated on 11 November 2019.</p>
<div id="introduction" class="section level1">
<h1 class="hasAnchor">
<a href="#introduction" class="anchor"></a>Introduction</h1>
@ -212,21 +212,21 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2019-11-10</td>
<td align="center">2019-11-11</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">2019-11-10</td>
<td align="center">2019-11-11</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">2019-11-10</td>
<td align="center">2019-11-11</td>
<td align="center">efgh</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
@ -321,71 +321,71 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2015-05-08</td>
<td align="center">P3</td>
<td align="center">2011-09-25</td>
<td align="center">O7</td>
<td align="center">Hospital C</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2012-04-04</td>
<td align="center">O9</td>
<td align="center">Hospital A</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2015-03-11</td>
<td align="center">S3</td>
<td align="center">Hospital A</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2017-11-03</td>
<td align="center">Y8</td>
<td align="center">Hospital C</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2013-09-06</td>
<td align="center">U9</td>
<td align="center">Hospital B</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2015-11-16</td>
<td align="center">E7</td>
<td align="center">2014-12-11</td>
<td align="center">G1</td>
<td align="center">Hospital B</td>
<td align="center">Escherichia coli</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="odd">
<td align="center">2011-04-18</td>
<td align="center">F4</td>
<td align="center">Hospital B</td>
<td align="center">Streptococcus pneumoniae</td>
<td align="center">S</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="even">
<td align="center">2010-04-22</td>
<td align="center">L4</td>
<td align="center">2013-01-02</td>
<td align="center">J8</td>
<td align="center">Hospital D</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="even">
<td align="center">2014-08-17</td>
<td align="center">S8</td>
<td align="center">Hospital C</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
</tbody>
</table>
<p>Now, let’s start the cleaning and the analysis!</p>
@ -406,8 +406,8 @@
#
# Item Count Percent Cum. Count Cum. Percent
# --- ----- ------- -------- ----------- -------------
# 1 M 10,417 52.09% 10,417 52.09%
# 2 F 9,583 47.92% 20,000 100.00%</code></pre>
# 1 M 10,427 52.14% 10,427 52.14%
# 2 F 9,573 47.87% 20,000 100.00%</code></pre>
<p>So, we can draw at least two conclusions immediately. From a data scientists perspective, the data looks clean: only values <code>M</code> and <code>F</code>. From a researchers perspective: there are slightly more men. Nothing we didn’t already know.</p>
<p>The data is already quite clean, but we still need to transform some variables. The <code>bacteria</code> column now consists of text, and we want to add more variables based on microbial IDs later on. So, we will transform this column to valid IDs. The <code><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate()</a></code> function of the <code>dplyr</code> package makes this really easy:</p>
<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb12-1" data-line-number="1">data &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span></a>
@ -437,14 +437,14 @@
<a class="sourceLine" id="cb14-18" data-line-number="18"><span class="co"># Pasteurella multocida (no changes)</span></a>
<a class="sourceLine" id="cb14-19" data-line-number="19"><span class="co"># Staphylococcus (no changes)</span></a>
<a class="sourceLine" id="cb14-20" data-line-number="20"><span class="co"># Streptococcus groups A, B, C, G (no changes)</span></a>
<a class="sourceLine" id="cb14-21" data-line-number="21"><span class="co"># Streptococcus pneumoniae (1,545 values changed)</span></a>
<a class="sourceLine" id="cb14-21" data-line-number="21"><span class="co"># Streptococcus pneumoniae (1,552 values changed)</span></a>
<a class="sourceLine" id="cb14-22" data-line-number="22"><span class="co"># Viridans group streptococci (no changes)</span></a>
<a class="sourceLine" id="cb14-23" data-line-number="23"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-24" data-line-number="24"><span class="co"># EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (v3.1, 2016)</span></a>
<a class="sourceLine" id="cb14-25" data-line-number="25"><span class="co"># Table 01: Intrinsic resistance in Enterobacteriaceae (1,309 values changed)</span></a>
<a class="sourceLine" id="cb14-25" data-line-number="25"><span class="co"># Table 01: Intrinsic resistance in Enterobacteriaceae (1,279 values changed)</span></a>
<a class="sourceLine" id="cb14-26" data-line-number="26"><span class="co"># Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb14-27" data-line-number="27"><span class="co"># Table 03: Intrinsic resistance in other Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb14-28" data-line-number="28"><span class="co"># Table 04: Intrinsic resistance in Gram-positive bacteria (2,733 values changed)</span></a>
<a class="sourceLine" id="cb14-28" data-line-number="28"><span class="co"># Table 04: Intrinsic resistance in Gram-positive bacteria (2,800 values changed)</span></a>
<a class="sourceLine" id="cb14-29" data-line-number="29"><span class="co"># Table 08: Interpretive rules for B-lactam agents and Gram-positive cocci (no changes)</span></a>
<a class="sourceLine" id="cb14-30" data-line-number="30"><span class="co"># Table 09: Interpretive rules for B-lactam agents and Gram-negative rods (no changes)</span></a>
<a class="sourceLine" id="cb14-31" data-line-number="31"><span class="co"># Table 11: Interpretive rules for macrolides, lincosamides, and streptogramins (no changes)</span></a>
@ -452,23 +452,23 @@
<a class="sourceLine" id="cb14-33" data-line-number="33"><span class="co"># Table 13: Interpretive rules for quinolones (no changes)</span></a>
<a class="sourceLine" id="cb14-34" data-line-number="34"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-35" data-line-number="35"><span class="co"># Other rules</span></a>
<a class="sourceLine" id="cb14-36" data-line-number="36"><span class="co"># Non-EUCAST: amoxicillin/clav acid = S where ampicillin = S (2,194 values changed)</span></a>
<a class="sourceLine" id="cb14-37" data-line-number="37"><span class="co"># Non-EUCAST: ampicillin = R where amoxicillin/clav acid = R (121 values changed)</span></a>
<a class="sourceLine" id="cb14-36" data-line-number="36"><span class="co"># Non-EUCAST: amoxicillin/clav acid = S where ampicillin = S (2,257 values changed)</span></a>
<a class="sourceLine" id="cb14-37" data-line-number="37"><span class="co"># Non-EUCAST: ampicillin = R where amoxicillin/clav acid = R (132 values changed)</span></a>
<a class="sourceLine" id="cb14-38" data-line-number="38"><span class="co"># Non-EUCAST: piperacillin = R where piperacillin/tazobactam = R (no changes)</span></a>
<a class="sourceLine" id="cb14-39" data-line-number="39"><span class="co"># Non-EUCAST: piperacillin/tazobactam = S where piperacillin = S (no changes)</span></a>
<a class="sourceLine" id="cb14-40" data-line-number="40"><span class="co"># Non-EUCAST: trimethoprim = R where trimethoprim/sulfa = R (no changes)</span></a>
<a class="sourceLine" id="cb14-41" data-line-number="41"><span class="co"># Non-EUCAST: trimethoprim/sulfa = S where trimethoprim = S (no changes)</span></a>
<a class="sourceLine" id="cb14-42" data-line-number="42"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-43" data-line-number="43"><span class="co"># --------------------------------------------------------------------------</span></a>
<a class="sourceLine" id="cb14-44" data-line-number="44"><span class="co"># EUCAST rules affected 6,489 out of 20,000 rows, making a total of 7,902 edits</span></a>
<a class="sourceLine" id="cb14-44" data-line-number="44"><span class="co"># EUCAST rules affected 6,599 out of 20,000 rows, making a total of 8,020 edits</span></a>
<a class="sourceLine" id="cb14-45" data-line-number="45"><span class="co"># =&gt; added 0 test results</span></a>
<a class="sourceLine" id="cb14-46" data-line-number="46"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-47" data-line-number="47"><span class="co"># =&gt; changed 7,902 test results</span></a>
<a class="sourceLine" id="cb14-48" data-line-number="48"><span class="co"># - 118 test results changed from S to I</span></a>
<a class="sourceLine" id="cb14-49" data-line-number="49"><span class="co"># - 4,776 test results changed from S to R</span></a>
<a class="sourceLine" id="cb14-50" data-line-number="50"><span class="co"># - 1,063 test results changed from I to S</span></a>
<a class="sourceLine" id="cb14-51" data-line-number="51"><span class="co"># - 318 test results changed from I to R</span></a>
<a class="sourceLine" id="cb14-52" data-line-number="52"><span class="co"># - 1,603 test results changed from R to S</span></a>
<a class="sourceLine" id="cb14-47" data-line-number="47"><span class="co"># =&gt; changed 8,020 test results</span></a>
<a class="sourceLine" id="cb14-48" data-line-number="48"><span class="co"># - 119 test results changed from S to I</span></a>
<a class="sourceLine" id="cb14-49" data-line-number="49"><span class="co"># - 4,832 test results changed from S to R</span></a>
<a class="sourceLine" id="cb14-50" data-line-number="50"><span class="co"># - 1,096 test results changed from I to S</span></a>
<a class="sourceLine" id="cb14-51" data-line-number="51"><span class="co"># - 342 test results changed from I to R</span></a>
<a class="sourceLine" id="cb14-52" data-line-number="52"><span class="co"># - 1,607 test results changed from R to S</span></a>
<a class="sourceLine" id="cb14-53" data-line-number="53"><span class="co"># - 24 test results changed from R to I</span></a>
<a class="sourceLine" id="cb14-54" data-line-number="54"><span class="co"># --------------------------------------------------------------------------</span></a>
<a class="sourceLine" id="cb14-55" data-line-number="55"><span class="co"># </span></a>
@ -497,8 +497,8 @@
<a class="sourceLine" id="cb16-3" data-line-number="3"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `bacteria` as input for `col_mo`.</span></a>
<a class="sourceLine" id="cb16-4" data-line-number="4"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `date` as input for `col_date`.</span></a>
<a class="sourceLine" id="cb16-5" data-line-number="5"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
<a class="sourceLine" id="cb16-6" data-line-number="6"><span class="co"># =&gt; Found 5,696 first isolates (28.5% of total)</span></a></code></pre></div>
<p>So only 28.5% is suitable for resistance analysis! We can now filter on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
<a class="sourceLine" id="cb16-6" data-line-number="6"><span class="co"># =&gt; Found 5,657 first isolates (28.3% of total)</span></a></code></pre></div>
<p>So only 28.3% is suitable for resistance analysis! We can now filter on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb17-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb17-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(first <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>)</a></code></pre></div>
<p>For future use, the above two syntaxes can be shortened with the <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> function:</p>
@ -508,7 +508,7 @@
<div id="first-weighted-isolates" class="section level2">
<h2 class="hasAnchor">
<a href="#first-weighted-isolates" class="anchor"></a>First <em>weighted</em> isolates</h2>
<p>We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient P1, sorted on date:</p>
<p>We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient D2, sorted on date:</p>
<table class="table">
<thead><tr class="header">
<th align="center">isolate</th>
@ -524,19 +524,19 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-01-26</td>
<td align="center">P1</td>
<td align="center">2010-02-14</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-04-19</td>
<td align="center">P1</td>
<td align="center">2010-04-27</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -546,30 +546,30 @@
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-04-24</td>
<td align="center">P1</td>
<td align="center">2010-05-31</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-06-11</td>
<td align="center">P1</td>
<td align="center">2010-08-21</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2010-11-24</td>
<td align="center">P1</td>
<td align="center">2010-09-21</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -579,8 +579,8 @@
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2010-12-11</td>
<td align="center">P1</td>
<td align="center">2010-10-04</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
@ -590,8 +590,8 @@
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2010-12-23</td>
<td align="center">P1</td>
<td align="center">2010-10-11</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -601,10 +601,10 @@
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2011-01-14</td>
<td align="center">P1</td>
<td align="center">2010-11-16</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
@ -612,26 +612,26 @@
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-01-19</td>
<td align="center">P1</td>
<td align="center">2011-03-05</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-01-26</td>
<td align="center">P1</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-04-18</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
</tbody>
</table>
<p>Only 2 isolates are marked as ‘first’ according to CLSI guideline. But when reviewing the antibiogram, it is obvious that some isolates are absolutely different strains and should be included too. This is why we weigh isolates, based on their antibiogram. The <code><a href="../reference/key_antibiotics.html">key_antibiotics()</a></code> function adds a vector with 18 key antibiotics: 6 broad spectrum ones, 6 small spectrum for Gram negatives and 6 small spectrum for Gram positives. These can be defined by the user.</p>
@ -645,7 +645,7 @@
<a class="sourceLine" id="cb19-7" data-line-number="7"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
<a class="sourceLine" id="cb19-8" data-line-number="8"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `keyab` as input for `col_keyantibiotics`. Use col_keyantibiotics = FALSE to prevent this.</span></a>
<a class="sourceLine" id="cb19-9" data-line-number="9"><span class="co"># [Criterion] Inclusion based on key antibiotics, ignoring I</span></a>
<a class="sourceLine" id="cb19-10" data-line-number="10"><span class="co"># =&gt; Found 15,241 first weighted isolates (76.2% of total)</span></a></code></pre></div>
<a class="sourceLine" id="cb19-10" data-line-number="10"><span class="co"># =&gt; Found 15,009 first weighted isolates (75.0% of total)</span></a></code></pre></div>
<table class="table">
<thead><tr class="header">
<th align="center">isolate</th>
@ -662,20 +662,20 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-01-26</td>
<td align="center">P1</td>
<td align="center">2010-02-14</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-04-19</td>
<td align="center">P1</td>
<td align="center">2010-04-27</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -686,44 +686,44 @@
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-04-24</td>
<td align="center">P1</td>
<td align="center">2010-05-31</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-06-11</td>
<td align="center">P1</td>
<td align="center">2010-08-21</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2010-11-24</td>
<td align="center">P1</td>
<td align="center">2010-09-21</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2010-12-11</td>
<td align="center">P1</td>
<td align="center">2010-10-04</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
@ -734,8 +734,8 @@
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2010-12-23</td>
<td align="center">P1</td>
<td align="center">2010-10-11</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -746,10 +746,10 @@
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2011-01-14</td>
<td align="center">P1</td>
<td align="center">2010-11-16</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
@ -758,35 +758,35 @@
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-01-19</td>
<td align="center">P1</td>
<td align="center">2011-03-05</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-04-18</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-01-26</td>
<td align="center">P1</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
</tr>
</tbody>
</table>
<p>Instead of 2, now 10 isolates are flagged. In total, 76.2% of all isolates are marked ‘first weighted’ - 47.7% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
<p>Instead of 2, now 8 isolates are flagged. In total, 75.0% of all isolates are marked ‘first weighted’ - 46.8% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
<p>As with <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code>, there’s a shortcut for this new algorithm too:</p>
<div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb20-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/first_isolate.html">filter_first_weighted_isolate</a></span>()</a></code></pre></div>
<p>So we end up with 15,241 isolates for analysis.</p>
<p>So we end up with 15,009 isolates for analysis.</p>
<p>We can remove unneeded columns:</p>
<div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb21-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb21-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span><span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(first, keyab))</a></code></pre></div>
@ -812,57 +812,9 @@
<tbody>
<tr class="odd">
<td>1</td>
<td align="center">2015-05-08</td>
<td align="center">P3</td>
<td align="center">Hospital A</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td>3</td>
<td align="center">2013-09-06</td>
<td align="center">U9</td>
<td align="center">Hospital B</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td>5</td>
<td align="center">2011-04-18</td>
<td align="center">F4</td>
<td align="center">Hospital B</td>
<td align="center">B_STRPT_PNMN</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">M</td>
<td align="center">Gram-positive</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td>7</td>
<td align="center">2016-10-10</td>
<td align="center">S10</td>
<td align="center">Hospital D</td>
<td align="center">2011-09-25</td>
<td align="center">O7</td>
<td align="center">Hospital C</td>
<td align="center">B_STPHY_AURS</td>
<td align="center">S</td>
<td align="center">S</td>
@ -874,36 +826,84 @@
<td align="center">aureus</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td>8</td>
<td align="center">2010-01-21</td>
<td align="center">R3</td>
<td align="center">Hospital B</td>
<td align="center">B_STRPT_PNMN</td>
<tr class="even">
<td>3</td>
<td align="center">2015-03-11</td>
<td align="center">S3</td>
<td align="center">Hospital A</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">F</td>
<td align="center">Gram-positive</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td>4</td>
<td align="center">2014-12-11</td>
<td align="center">G1</td>
<td align="center">Hospital B</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td>5</td>
<td align="center">2013-01-02</td>
<td align="center">J8</td>
<td align="center">Hospital D</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">M</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td>7</td>
<td align="center">2013-08-06</td>
<td align="center">H4</td>
<td align="center">Hospital B</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">I</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td>9</td>
<td align="center">2011-11-23</td>
<td align="center">B7</td>
<td align="center">Hospital B</td>
<td align="center">B_STRPT_PNMN</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">2016-10-03</td>
<td align="center">F3</td>
<td align="center">Hospital D</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">Gram-positive</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
</tbody>
@ -925,7 +925,7 @@
<div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb24-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(genus, species)</a></code></pre></div>
<p><strong>Frequency table</strong></p>
<p>Class: character<br>
Length: 15,241 (of which NA: 0 = 0%)<br>
Length: 15,009 (of which NA: 0 = 0%)<br>
Unique: 4</p>
<p>Shortest: 16<br>
Longest: 24</p>
@ -942,33 +942,33 @@ Longest: 24</p>
<tr class="odd">
<td align="left">1</td>
<td align="left">Escherichia coli</td>
<td align="right">7,593</td>
<td align="right">49.82%</td>
<td align="right">7,593</td>
<td align="right">49.82%</td>
<td align="right">7,411</td>
<td align="right">49.38%</td>
<td align="right">7,411</td>
<td align="right">49.38%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Staphylococcus aureus</td>
<td align="right">3,734</td>
<td align="right">24.50%</td>
<td align="right">11,327</td>
<td align="right">74.32%</td>
<td align="right">3,707</td>
<td align="right">24.70%</td>
<td align="right">11,118</td>
<td align="right">74.08%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Streptococcus pneumoniae</td>
<td align="right">2,327</td>
<td align="right">15.27%</td>
<td align="right">13,654</td>
<td align="right">89.59%</td>
<td align="right">2,318</td>
<td align="right">15.44%</td>
<td align="right">13,436</td>
<td align="right">89.52%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Klebsiella pneumoniae</td>
<td align="right">1,587</td>
<td align="right">10.41%</td>
<td align="right">15,241</td>
<td align="right">1,573</td>
<td align="right">10.48%</td>
<td align="right">15,009</td>
<td align="right">100.00%</td>
</tr>
</tbody>
@ -980,7 +980,7 @@ Longest: 24</p>
<p>The functions <code><a href="../reference/proportion.html">resistance()</a></code> and <code><a href="../reference/proportion.html">susceptibility()</a></code> can be used to calculate antimicrobial resistance or susceptibility. For more specific analyses, the functions <code><a href="../reference/proportion.html">proportion_S()</a></code>, <code><a href="../reference/proportion.html">proportion_SI()</a></code>, <code><a href="../reference/proportion.html">proportion_I()</a></code>, <code><a href="../reference/proportion.html">proportion_IR()</a></code> and <code><a href="../reference/proportion.html">proportion_R()</a></code> can be used to determine the proportion of a specific antimicrobial outcome.</p>
<p>As per the EUCAST guideline of 2019, we calculate resistance as the proportion of R (<code><a href="../reference/proportion.html">proportion_R()</a></code>, equal to <code><a href="../reference/proportion.html">resistance()</a></code>) and susceptibility as the proportion of S and I (<code><a href="../reference/proportion.html">proportion_SI()</a></code>, equal to <code><a href="../reference/proportion.html">susceptibility()</a></code>). These functions can be used on their own:</p>
<div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb25-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/proportion.html">resistance</a></span>(AMX)</a>
<a class="sourceLine" id="cb25-2" data-line-number="2"><span class="co"># [1] 0.4724099</span></a></code></pre></div>
<a class="sourceLine" id="cb25-2" data-line-number="2"><span class="co"># [1] 0.4684523</span></a></code></pre></div>
<p>Or can be used in conjuction with <code><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise()</a></code>, both from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb26-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb26-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital) <span class="op">%&gt;%</span><span class="st"> </span></a>
@ -993,19 +993,19 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4637681</td>
<td align="center">0.4640823</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4776811</td>
<td align="center">0.4663609</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4811697</td>
<td align="center">0.4736130</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4694820</td>
<td align="center">0.4749499</td>
</tr>
</tbody>
</table>
@ -1023,23 +1023,23 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4637681</td>
<td align="center">4554</td>
<td align="center">0.4640823</td>
<td align="center">4566</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4776811</td>
<td align="center">5399</td>
<td align="center">0.4663609</td>
<td align="center">5232</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4811697</td>
<td align="center">2257</td>
<td align="center">0.4736130</td>
<td align="center">2217</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4694820</td>
<td align="center">3031</td>
<td align="center">0.4749499</td>
<td align="center">2994</td>
</tr>
</tbody>
</table>
@ -1059,27 +1059,27 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Escherichia</td>
<td align="center">0.9212433</td>
<td align="center">0.8984591</td>
<td align="center">0.9927565</td>
<td align="center">0.9211982</td>
<td align="center">0.8896235</td>
<td align="center">0.9929834</td>
</tr>
<tr class="even">
<td align="center">Klebsiella</td>
<td align="center">0.8298677</td>
<td align="center">0.8897290</td>
<td align="center">0.9836169</td>
<td align="center">0.8239034</td>
<td align="center">0.8804832</td>
<td align="center">0.9809282</td>
</tr>
<tr class="odd">
<td align="center">Staphylococcus</td>
<td align="center">0.9290305</td>
<td align="center">0.9258168</td>
<td align="center">0.9946438</td>
<td align="center">0.9188023</td>
<td align="center">0.9209603</td>
<td align="center">0.9932560</td>
</tr>
<tr class="even">
<td align="center">Streptococcus</td>
<td align="center">0.6067899</td>
<td align="center">0.5974978</td>
<td align="center">0.0000000</td>
<td align="center">0.6067899</td>
<td align="center">0.5974978</td>
</tr>
</tbody>
</table>
@ -1089,11 +1089,12 @@ Longest: 24</p>
<a class="sourceLine" id="cb29-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise</a></span>(<span class="st">"1. Amoxi/clav"</span> =<span class="st"> </span><span class="kw"><a href="../reference/proportion.html">susceptibility</a></span>(AMC),</a>
<a class="sourceLine" id="cb29-4" data-line-number="4"> <span class="st">"2. Gentamicin"</span> =<span class="st"> </span><span class="kw"><a href="../reference/proportion.html">susceptibility</a></span>(GEN),</a>
<a class="sourceLine" id="cb29-5" data-line-number="5"> <span class="st">"3. Amoxi/clav + genta"</span> =<span class="st"> </span><span class="kw"><a href="../reference/proportion.html">susceptibility</a></span>(AMC, GEN)) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb29-6" data-line-number="6"><span class="st"> </span>tidyr<span class="op">::</span><span class="kw"><a href="https://tidyr.tidyverse.org/reference/gather.html">gather</a></span>(<span class="st">"antibiotic"</span>, <span class="st">"S"</span>, <span class="op">-</span>genus) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb29-7" data-line-number="7"><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></span>(<span class="kw"><a href="https://ggplot2.tidyverse.org/reference/aes.html">aes</a></span>(<span class="dt">x =</span> genus,</a>
<a class="sourceLine" id="cb29-8" data-line-number="8"> <span class="dt">y =</span> S,</a>
<a class="sourceLine" id="cb29-9" data-line-number="9"> <span class="dt">fill =</span> antibiotic)) <span class="op">+</span></a>
<a class="sourceLine" id="cb29-10" data-line-number="10"><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/geom_bar.html">geom_col</a></span>(<span class="dt">position =</span> <span class="st">"dodge2"</span>)</a></code></pre></div>
<a class="sourceLine" id="cb29-6" data-line-number="6"><span class="st"> </span><span class="co"># pivot_longer() from the tidyr package "lengthens" data:</span></a>
<a class="sourceLine" id="cb29-7" data-line-number="7"><span class="st"> </span>tidyr<span class="op">::</span><span class="kw"><a href="https://tidyr.tidyverse.org/reference/pivot_longer.html">pivot_longer</a></span>(<span class="op">-</span>genus, <span class="dt">names_to =</span> <span class="st">"antibiotic"</span>) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb29-8" data-line-number="8"><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></span>(<span class="kw"><a href="https://ggplot2.tidyverse.org/reference/aes.html">aes</a></span>(<span class="dt">x =</span> genus,</a>
<a class="sourceLine" id="cb29-9" data-line-number="9"> <span class="dt">y =</span> value,</a>
<a class="sourceLine" id="cb29-10" data-line-number="10"> <span class="dt">fill =</span> antibiotic)) <span class="op">+</span></a>
<a class="sourceLine" id="cb29-11" data-line-number="11"><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/geom_bar.html">geom_col</a></span>(<span class="dt">position =</span> <span class="st">"dodge2"</span>)</a></code></pre></div>
<p><img src="AMR_files/figure-html/plot%201-1.png" width="720"></p>
</div>
<div id="plots" class="section level2">
@ -1154,19 +1155,24 @@ Longest: 24</p>
<a href="#independence-test" class="anchor"></a>Independence test</h2>
<p>The next example uses the included <code>example_isolates</code>, which is an anonymised data set containing 2,000 microbial blood culture isolates with their full antibiograms found in septic patients in 4 different hospitals in the Netherlands, between 2001 and 2017. This <code>data.frame</code> can be used to practice AMR analysis.</p>
<p>We will compare the resistance to fosfomycin (column <code>FOS</code>) in hospital A and D. The input for the <code><a href="https://rdrr.io/r/stats/fisher.test.html">fisher.test()</a></code> can be retrieved with a transformation like this:</p>
<div class="sourceCode" id="cb34"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb34-1" data-line-number="1">check_FOS &lt;-<span class="st"> </span>example_isolates <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb34-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(hospital_id <span class="op">%in%</span><span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"A"</span>, <span class="st">"D"</span>)) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># filter on only hospitals A and D</span></a>
<a class="sourceLine" id="cb34-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(hospital_id, FOS) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># select the hospitals and fosfomycin</span></a>
<a class="sourceLine" id="cb34-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># group on the hospitals</span></a>
<a class="sourceLine" id="cb34-5" data-line-number="5"><span class="st"> </span><span class="kw"><a href="../reference/count.html">count_df</a></span>(<span class="dt">combine_SI =</span> <span class="ot">TRUE</span>) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># count all isolates per group (hospital_id)</span></a>
<a class="sourceLine" id="cb34-6" data-line-number="6"><span class="st"> </span>tidyr<span class="op">::</span><span class="kw"><a href="https://tidyr.tidyverse.org/reference/spread.html">spread</a></span>(hospital_id, value) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># transform output so A and D are columns</span></a>
<a class="sourceLine" id="cb34-7" data-line-number="7"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(A, D) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># and select these only</span></a>
<a class="sourceLine" id="cb34-8" data-line-number="8"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/matrix.html">as.matrix</a></span>() <span class="co"># transform to good old matrix for fisher.test()</span></a>
<a class="sourceLine" id="cb34-9" data-line-number="9"></a>
<a class="sourceLine" id="cb34-10" data-line-number="10">check_FOS</a>
<a class="sourceLine" id="cb34-11" data-line-number="11"><span class="co"># A D</span></a>
<a class="sourceLine" id="cb34-12" data-line-number="12"><span class="co"># [1,] 25 77</span></a>
<a class="sourceLine" id="cb34-13" data-line-number="13"><span class="co"># [2,] 24 33</span></a></code></pre></div>
<div class="sourceCode" id="cb34"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb34-1" data-line-number="1"><span class="co"># use package 'tidyr' to pivot data; </span></a>
<a class="sourceLine" id="cb34-2" data-line-number="2"><span class="co"># it gets installed with this 'AMR' package</span></a>
<a class="sourceLine" id="cb34-3" data-line-number="3"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(tidyr)</a>
<a class="sourceLine" id="cb34-4" data-line-number="4"></a>
<a class="sourceLine" id="cb34-5" data-line-number="5">check_FOS &lt;-<span class="st"> </span>example_isolates <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb34-6" data-line-number="6"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(hospital_id <span class="op">%in%</span><span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"A"</span>, <span class="st">"D"</span>)) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># filter on only hospitals A and D</span></a>
<a class="sourceLine" id="cb34-7" data-line-number="7"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(hospital_id, FOS) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># select the hospitals and fosfomycin</span></a>
<a class="sourceLine" id="cb34-8" data-line-number="8"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># group on the hospitals</span></a>
<a class="sourceLine" id="cb34-9" data-line-number="9"><span class="st"> </span><span class="kw"><a href="../reference/count.html">count_df</a></span>(<span class="dt">combine_SI =</span> <span class="ot">TRUE</span>) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># count all isolates per group (hospital_id)</span></a>
<a class="sourceLine" id="cb34-10" data-line-number="10"><span class="st"> </span><span class="kw"><a href="https://tidyr.tidyverse.org/reference/pivot_wider.html">pivot_wider</a></span>(<span class="dt">names_from =</span> hospital_id, <span class="co"># transform output so A and D are columns</span></a>
<a class="sourceLine" id="cb34-11" data-line-number="11"> <span class="dt">values_from =</span> value) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb34-12" data-line-number="12"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(A, D) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># and only select these columns</span></a>
<a class="sourceLine" id="cb34-13" data-line-number="13"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/matrix.html">as.matrix</a></span>() <span class="co"># transform to a good old matrix for fisher.test()</span></a>
<a class="sourceLine" id="cb34-14" data-line-number="14"></a>
<a class="sourceLine" id="cb34-15" data-line-number="15">check_FOS</a>
<a class="sourceLine" id="cb34-16" data-line-number="16"><span class="co"># A D</span></a>
<a class="sourceLine" id="cb34-17" data-line-number="17"><span class="co"># [1,] 25 77</span></a>
<a class="sourceLine" id="cb34-18" data-line-number="18"><span class="co"># [2,] 24 33</span></a></code></pre></div>
<p>We can apply the test now with:</p>
<div class="sourceCode" id="cb35"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb35-1" data-line-number="1"><span class="co"># do Fisher's Exact Test</span></a>
<a class="sourceLine" id="cb35-2" data-line-number="2"><span class="kw"><a href="https://rdrr.io/r/stats/fisher.test.html">fisher.test</a></span>(check_FOS) </a>
@ -1181,7 +1187,7 @@ Longest: 24</p>
<a class="sourceLine" id="cb35-11" data-line-number="11"><span class="co"># sample estimates:</span></a>
<a class="sourceLine" id="cb35-12" data-line-number="12"><span class="co"># odds ratio </span></a>
<a class="sourceLine" id="cb35-13" data-line-number="13"><span class="co"># 0.4488318</span></a></code></pre></div>
<p>As can be seen, the p value is 0.031, which means that the fosfomycin resistances found in hospital A and D are really different.</p>
<p>As can be seen, the p value is 0.031, which means that the fosfomycin resistance found in hospital A and D are really different.</p>
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@ -41,7 +41,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9030</span>
</span>
</div>
@ -187,7 +187,7 @@
<h1>How to import data from SPSS / SAS / Stata</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">16 October 2019</h4>
<h4 class="date">11 November 2019</h4>
<div class="hidden name"><code>SPSS.Rmd</code></div>
@ -213,7 +213,7 @@
</li>
<li>
<p><strong>R is extremely flexible.</strong></p>
<p>Because you write the syntax yourself, you can do anything you want. The flexibility in transforming, gathering, grouping and summarising data, or drawing plots, is endless - with SPSS, SAS or Stata you are bound to their algorithms and format styles. They may be a bit flexible, but you can probably never create that very specific publication-ready plot without using other (paid) software. If you sometimes write syntaxes in SPSS to run a complete analysis or to ‘automate’ some of your work, you could do this a lot less time in R. You will notice that writing syntaxes in R is a lot more nifty and clever than in SPSS. Still, as working with any statistical package, you will have to have knowledge about what you are doing (statistically) and what you are willing to accomplish.</p>
<p>Because you write the syntax yourself, you can do anything you want. The flexibility in transforming, arranging, grouping and summarising data, or drawing plots, is endless - with SPSS, SAS or Stata you are bound to their algorithms and format styles. They may be a bit flexible, but you can probably never create that very specific publication-ready plot without using other (paid) software. If you sometimes write syntaxes in SPSS to run a complete analysis or to ‘automate’ some of your work, you could do this a lot less time in R. You will notice that writing syntaxes in R is a lot more nifty and clever than in SPSS. Still, as working with any statistical package, you will have to have knowledge about what you are doing (statistically) and what you are willing to accomplish.</p>
</li>
<li>
<p><strong>R can be easily automated.</strong></p>

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@ -84,7 +84,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9030</span>
</span>
</div>