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(v0.7.0.9001) new pathovars, small fixes

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@ -40,7 +40,7 @@
</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="Released version">0.7.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.7.0.9000</span>
</span>
</div>
@ -199,7 +199,7 @@
<h1>How to conduct AMR analysis</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">03 June 2019</h4>
<h4 class="date">07 June 2019</h4>
<div class="hidden name"><code>AMR.Rmd</code></div>
@ -208,7 +208,7 @@
<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 03 June 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 07 June 2019.</p>
<div id="introduction" class="section level1">
<h1 class="hasAnchor">
<a href="#introduction" class="anchor"></a>Introduction</h1>
@ -224,21 +224,21 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2019-06-03</td>
<td align="center">2019-06-07</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">2019-06-03</td>
<td align="center">2019-06-07</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">2019-06-03</td>
<td align="center">2019-06-07</td>
<td align="center">efgh</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
@ -334,19 +334,52 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2010-12-01</td>
<td align="center">Y6</td>
<td align="center">Hospital C</td>
<td align="center">2010-01-26</td>
<td align="center">S3</td>
<td align="center">Hospital B</td>
<td align="center">Escherichia 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">F</td>
</tr>
<tr class="even">
<td align="center">2010-08-26</td>
<td align="center">G7</td>
<td align="center">Hospital D</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>
<td align="center">M</td>
</tr>
<tr class="odd">
<td align="center">2016-05-04</td>
<td align="center">B8</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">R</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="even">
<td align="center">2011-05-31</td>
<td align="center">C8</td>
<td align="center">2016-11-19</td>
<td align="center">E10</td>
<td align="center">Hospital D</td>
<td align="center">Streptococcus pneumoniae</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">2013-07-13</td>
<td align="center">G3</td>
<td align="center">Hospital A</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
@ -355,45 +388,12 @@
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="odd">
<td align="center">2012-04-18</td>
<td align="center">Z6</td>
<td align="center">Hospital D</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2011-04-24</td>
<td align="center">W4</td>
<td align="center">2017-05-23</td>
<td align="center">V3</td>
<td align="center">Hospital C</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2011-11-05</td>
<td align="center">A9</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">R</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="even">
<td align="center">2016-09-07</td>
<td align="center">Y6</td>
<td align="center">Hospital B</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>
@ -409,7 +409,7 @@
<a href="#cleaning-the-data" class="anchor"></a>Cleaning the data</h1>
<p>Use the frequency table function <code><a href="../reference/freq.html">freq()</a></code> to look specifically for unique values in any variable. For example, for the <code>gender</code> variable:</p>
<div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb10-1" title="1">data <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(gender) <span class="co"># this would be the same: freq(data$gender)</span></a></code></pre></div>
<pre><code># Frequency table of `gender` from a data.frame (20,000 x 9)
<pre><code># Frequency table of `gender` from `data` (20,000 x 9)
#
# Class: factor (numeric)
# Length: 20,000 (of which NA: 0 = 0.00%)
@ -418,8 +418,8 @@
#
# Item Count Percent Cum. Count Cum. Percent
# --- ----- ------- -------- ----------- -------------
# 1 M 10,407 52.0% 10,407 52.0%
# 2 F 9,593 48.0% 20,000 100.0%</code></pre>
# 1 M 10,368 51.8% 10,368 51.8%
# 2 F 9,632 48.2% 20,000 100.0%</code></pre>
<p>So, we can draw at least two conclusions immediately. From a data scientist perspective, the data looks clean: only values <code>M</code> and <code>F</code>. From a researcher 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" title="1">data &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span></a>
@ -449,14 +449,14 @@
<a class="sourceLine" id="cb14-18" title="18"><span class="co"># Pasteurella multocida (no new changes)</span></a>
<a class="sourceLine" id="cb14-19" title="19"><span class="co"># Staphylococcus (no new changes)</span></a>
<a class="sourceLine" id="cb14-20" title="20"><span class="co"># Streptococcus groups A, B, C, G (no new changes)</span></a>
<a class="sourceLine" id="cb14-21" title="21"><span class="co"># Streptococcus pneumoniae (1431 new changes)</span></a>
<a class="sourceLine" id="cb14-21" title="21"><span class="co"># Streptococcus pneumoniae (1,496 new changes)</span></a>
<a class="sourceLine" id="cb14-22" title="22"><span class="co"># Viridans group streptococci (no new changes)</span></a>
<a class="sourceLine" id="cb14-23" title="23"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-24" title="24"><span class="co"># EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (v3.1, 2016)</span></a>
<a class="sourceLine" id="cb14-25" title="25"><span class="co"># Table 01: Intrinsic resistance in Enterobacteriaceae (1230 new changes)</span></a>
<a class="sourceLine" id="cb14-25" title="25"><span class="co"># Table 01: Intrinsic resistance in Enterobacteriaceae (1,276 new changes)</span></a>
<a class="sourceLine" id="cb14-26" title="26"><span class="co"># Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria (no new changes)</span></a>
<a class="sourceLine" id="cb14-27" title="27"><span class="co"># Table 03: Intrinsic resistance in other Gram-negative bacteria (no new changes)</span></a>
<a class="sourceLine" id="cb14-28" title="28"><span class="co"># Table 04: Intrinsic resistance in Gram-positive bacteria (2646 new changes)</span></a>
<a class="sourceLine" id="cb14-28" title="28"><span class="co"># Table 04: Intrinsic resistance in Gram-positive bacteria (2,809 new changes)</span></a>
<a class="sourceLine" id="cb14-29" title="29"><span class="co"># Table 08: Interpretive rules for B-lactam agents and Gram-positive cocci (no new changes)</span></a>
<a class="sourceLine" id="cb14-30" title="30"><span class="co"># Table 09: Interpretive rules for B-lactam agents and Gram-negative rods (no new changes)</span></a>
<a class="sourceLine" id="cb14-31" title="31"><span class="co"># Table 11: Interpretive rules for macrolides, lincosamides, and streptogramins (no new changes)</span></a>
@ -464,24 +464,24 @@
<a class="sourceLine" id="cb14-33" title="33"><span class="co"># Table 13: Interpretive rules for quinolones (no new changes)</span></a>
<a class="sourceLine" id="cb14-34" title="34"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-35" title="35"><span class="co"># Other rules</span></a>
<a class="sourceLine" id="cb14-36" title="36"><span class="co"># Non-EUCAST: amoxicillin/clav acid = S where ampicillin = S (2197 new changes)</span></a>
<a class="sourceLine" id="cb14-37" title="37"><span class="co"># Non-EUCAST: ampicillin = R where amoxicillin/clav acid = R (99 new changes)</span></a>
<a class="sourceLine" id="cb14-36" title="36"><span class="co"># Non-EUCAST: amoxicillin/clav acid = S where ampicillin = S (2,244 new changes)</span></a>
<a class="sourceLine" id="cb14-37" title="37"><span class="co"># Non-EUCAST: ampicillin = R where amoxicillin/clav acid = R (111 new changes)</span></a>
<a class="sourceLine" id="cb14-38" title="38"><span class="co"># Non-EUCAST: piperacillin = R where piperacillin/tazobactam = R (no new changes)</span></a>
<a class="sourceLine" id="cb14-39" title="39"><span class="co"># Non-EUCAST: piperacillin/tazobactam = S where piperacillin = S (no new changes)</span></a>
<a class="sourceLine" id="cb14-40" title="40"><span class="co"># Non-EUCAST: trimethoprim = R where trimethoprim/sulfa = R (no new changes)</span></a>
<a class="sourceLine" id="cb14-41" title="41"><span class="co"># Non-EUCAST: trimethoprim/sulfa = S where trimethoprim = S (no new changes)</span></a>
<a class="sourceLine" id="cb14-42" title="42"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-43" title="43"><span class="co"># --------------------------------------------------------------------------</span></a>
<a class="sourceLine" id="cb14-44" title="44"><span class="co"># EUCAST rules affected 6,284 out of 20,000 rows, making a total of 7,603 edits</span></a>
<a class="sourceLine" id="cb14-44" title="44"><span class="co"># EUCAST rules affected 6,565 out of 20,000 rows, making a total of 7,936 edits</span></a>
<a class="sourceLine" id="cb14-45" title="45"><span class="co"># =&gt; added 0 test results</span></a>
<a class="sourceLine" id="cb14-46" title="46"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-47" title="47"><span class="co"># =&gt; changed 7,603 test results</span></a>
<a class="sourceLine" id="cb14-48" title="48"><span class="co"># - 111 test results changed from S to I</span></a>
<a class="sourceLine" id="cb14-49" title="49"><span class="co"># - 4,561 test results changed from S to R</span></a>
<a class="sourceLine" id="cb14-50" title="50"><span class="co"># - 1,028 test results changed from I to S</span></a>
<a class="sourceLine" id="cb14-51" title="51"><span class="co"># - 292 test results changed from I to R</span></a>
<a class="sourceLine" id="cb14-52" title="52"><span class="co"># - 1,595 test results changed from R to S</span></a>
<a class="sourceLine" id="cb14-53" title="53"><span class="co"># - 16 test results changed from R to I</span></a>
<a class="sourceLine" id="cb14-47" title="47"><span class="co"># =&gt; changed 7,936 test results</span></a>
<a class="sourceLine" id="cb14-48" title="48"><span class="co"># - 116 test results changed from S to I</span></a>
<a class="sourceLine" id="cb14-49" title="49"><span class="co"># - 4,801 test results changed from S to R</span></a>
<a class="sourceLine" id="cb14-50" title="50"><span class="co"># - 1,059 test results changed from I to S</span></a>
<a class="sourceLine" id="cb14-51" title="51"><span class="co"># - 347 test results changed from I to R</span></a>
<a class="sourceLine" id="cb14-52" title="52"><span class="co"># - 1,596 test results changed from R to S</span></a>
<a class="sourceLine" id="cb14-53" title="53"><span class="co"># - 17 test results changed from R to I</span></a>
<a class="sourceLine" id="cb14-54" title="54"><span class="co"># --------------------------------------------------------------------------</span></a>
<a class="sourceLine" id="cb14-55" title="55"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-56" title="56"><span class="co"># Use verbose = TRUE to get a data.frame with all specified edits instead.</span></a></code></pre></div>
@ -509,8 +509,8 @@
<a class="sourceLine" id="cb16-3" title="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" title="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" title="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" title="6"><span class="co"># =&gt; Found 5,652 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>
<a class="sourceLine" id="cb16-6" title="6"><span class="co"># =&gt; Found 5,692 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>
<div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb17-1" title="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" title="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>
@ -536,8 +536,8 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-03-08</td>
<td align="center">C7</td>
<td align="center">2010-01-16</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
@ -547,10 +547,10 @@
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-04-14</td>
<td align="center">C7</td>
<td align="center">2010-02-23</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</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>
@ -558,8 +558,8 @@
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-04-18</td>
<td align="center">C7</td>
<td align="center">2010-04-05</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
@ -569,19 +569,19 @@
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-04-22</td>
<td align="center">C7</td>
<td align="center">2010-04-28</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</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">FALSE</td>
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2010-05-30</td>
<td align="center">C7</td>
<td align="center">2010-05-20</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
@ -591,19 +591,19 @@
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2010-10-09</td>
<td align="center">C7</td>
<td align="center">2010-07-07</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</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">7</td>
<td align="center">2011-01-26</td>
<td align="center">C7</td>
<td align="center">2010-09-11</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
@ -613,8 +613,8 @@
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2011-02-19</td>
<td align="center">C7</td>
<td align="center">2010-09-19</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
@ -624,29 +624,29 @@
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-03-25</td>
<td align="center">C7</td>
<td align="center">2010-10-07</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</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">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-04-17</td>
<td align="center">C7</td>
<td align="center">2011-01-14</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</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>
<p>Only 1 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>
<p>If a column exists with a name like ‘key(…)ab’ the <code><a href="../reference/first_isolate.html">first_isolate()</a></code> function will automatically use it and determine the first weighted isolates. Mind the NOTEs in below output:</p>
<div class="sourceCode" id="cb19"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb19-1" title="1">data &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb19-2" title="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">keyab =</span> <span class="kw"><a href="../reference/key_antibiotics.html">key_antibiotics</a></span>(.)) <span class="op">%&gt;%</span><span class="st"> </span></a>
@ -657,7 +657,7 @@
<a class="sourceLine" id="cb19-7" title="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" title="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" title="9"><span class="co"># [Criterion] Inclusion based on key antibiotics, ignoring I.</span></a>
<a class="sourceLine" id="cb19-10" title="10"><span class="co"># =&gt; Found 15,076 first weighted isolates (75.4% of total)</span></a></code></pre></div>
<a class="sourceLine" id="cb19-10" title="10"><span class="co"># =&gt; Found 15,072 first weighted isolates (75.4% of total)</span></a></code></pre></div>
<table class="table">
<thead><tr class="header">
<th align="center">isolate</th>
@ -674,8 +674,8 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-03-08</td>
<td align="center">C7</td>
<td align="center">2010-01-16</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
@ -686,68 +686,68 @@
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-04-14</td>
<td align="center">C7</td>
<td align="center">2010-02-23</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</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">FALSE</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-04-18</td>
<td align="center">C7</td>
<td align="center">2010-04-05</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</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">4</td>
<td align="center">2010-04-22</td>
<td align="center">C7</td>
<td align="center">2010-04-28</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</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">FALSE</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2010-05-30</td>
<td align="center">C7</td>
<td align="center">2010-05-20</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</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">2010-10-09</td>
<td align="center">C7</td>
<td align="center">2010-07-07</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</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">7</td>
<td align="center">2011-01-26</td>
<td align="center">C7</td>
<td align="center">2010-09-11</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
@ -758,8 +758,8 @@
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2011-02-19</td>
<td align="center">C7</td>
<td align="center">2010-09-19</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
@ -770,35 +770,35 @@
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-03-25</td>
<td align="center">C7</td>
<td align="center">2010-10-07</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</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>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-04-17</td>
<td align="center">C7</td>
<td align="center">2011-01-14</td>
<td align="center">V9</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
</tbody>
</table>
<p>Instead of 2, now 9 isolates are flagged. In total, 75.4% of all isolates are marked ‘first weighted’ - 47.1% 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 1, now 4 isolates are flagged. In total, 75.4% of all isolates are marked ‘first weighted’ - 46.9% 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" title="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" title="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 15,076 isolates for analysis.</p>
<p>So we end up with 15,072 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" title="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" title="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://www.rdocumentation.org/packages/base/topics/c">c</a></span>(first, keyab))</a></code></pre></div>
@ -806,6 +806,7 @@
<div class="sourceCode" id="cb22"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb22-1" title="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/head">head</a></span>(data_1st)</a></code></pre></div>
<table class="table">
<thead><tr class="header">
<th></th>
<th align="center">date</th>
<th align="center">patient_id</th>
<th align="center">hospital</th>
@ -822,13 +823,14 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2010-12-01</td>
<td align="center">Y6</td>
<td align="center">Hospital C</td>
<td>1</td>
<td align="center">2010-01-26</td>
<td align="center">S3</td>
<td align="center">Hospital B</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">I</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram negative</td>
@ -837,8 +839,41 @@
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2011-05-31</td>
<td align="center">C8</td>
<td>2</td>
<td align="center">2010-08-26</td>
<td align="center">G7</td>
<td align="center">Hospital D</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">R</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="odd">
<td>3</td>
<td align="center">2016-05-04</td>
<td align="center">B8</td>
<td align="center">Hospital A</td>
<td align="center">B_ESCHR_COL</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 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">2013-07-13</td>
<td align="center">G3</td>
<td align="center">Hospital A</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">R</td>
@ -852,63 +887,35 @@
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">2012-04-18</td>
<td align="center">Z6</td>
<td align="center">Hospital D</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</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 align="center">2011-04-24</td>
<td align="center">W4</td>
<td align="center">Hospital C</td>
<td align="center">B_STPHY_AUR</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram positive</td>
<td align="center">Staphylococcus</td>
<td align="center">aureus</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">2011-11-05</td>
<td align="center">A9</td>
<td align="center">Hospital C</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">R</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 negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2016-09-07</td>
<td>8</td>
<td align="center">2016-11-20</td>
<td align="center">Y6</td>
<td align="center">Hospital A</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</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>10</td>
<td align="center">2015-11-03</td>
<td align="center">W8</td>
<td align="center">Hospital B</td>
<td align="center">B_STPHY_AUR</td>
<td align="center">B_ESCHR_COL</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>
<td align="center">Gram positive</td>
<td align="center">Staphylococcus</td>
<td align="center">aureus</td>
<td align="center">Gram negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
</tbody>
@ -928,9 +935,9 @@
<div class="sourceCode" id="cb23"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb23-1" title="1"><span class="kw"><a href="../reference/freq.html">freq</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/paste">paste</a></span>(data_1st<span class="op">$</span>genus, data_1st<span class="op">$</span>species))</a></code></pre></div>
<p>Or can be used like the <code>dplyr</code> way, which is easier readable:</p>
<div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb24-1" title="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(genus, species)</a></code></pre></div>
<p><strong>Frequency table of <code>genus</code> and <code>species</code> from a <code>data.frame</code> (15,076 x 13)</strong></p>
<p><strong>Frequency table of <code>genus</code> and <code>species</code> from <code>data_1st</code> (15,072 x 13)</strong></p>
<p>Columns: 2<br>
Length: 15,076 (of which NA: 0 = 0.00%)<br>
Length: 15,072 (of which NA: 0 = 0.00%)<br>
Unique: 4</p>
<p>Shortest: 16<br>
Longest: 24</p>
@ -947,33 +954,33 @@ Longest: 24</p>
<tr class="odd">
<td align="left">1</td>
<td align="left">Escherichia coli</td>
<td align="right">7,402</td>
<td align="right">49.1%</td>
<td align="right">7,402</td>
<td align="right">49.1%</td>
<td align="right">7,451</td>
<td align="right">49.4%</td>
<td align="right">7,451</td>
<td align="right">49.4%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Staphylococcus aureus</td>
<td align="right">3,887</td>
<td align="right">25.8%</td>
<td align="right">11,289</td>
<td align="right">74.9%</td>
<td align="right">3,713</td>
<td align="right">24.6%</td>
<td align="right">11,164</td>
<td align="right">74.1%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Streptococcus pneumoniae</td>
<td align="right">2,244</td>
<td align="right">14.9%</td>
<td align="right">13,533</td>
<td align="right">2,367</td>
<td align="right">15.7%</td>
<td align="right">13,531</td>
<td align="right">89.8%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Klebsiella pneumoniae</td>
<td align="right">1,543</td>
<td align="right">1,541</td>
<td align="right">10.2%</td>
<td align="right">15,076</td>
<td align="right">15,072</td>
<td align="right">100.0%</td>
</tr>
</tbody>
@ -984,7 +991,7 @@ Longest: 24</p>
<a href="#resistance-percentages" class="anchor"></a>Resistance percentages</h2>
<p>The functions <code><a href="../reference/portion.html">portion_S()</a></code>, <code><a href="../reference/portion.html">portion_SI()</a></code>, <code><a href="../reference/portion.html">portion_I()</a></code>, <code><a href="../reference/portion.html">portion_IR()</a></code> and <code><a href="../reference/portion.html">portion_R()</a></code> can be used to determine the portion of a specific antimicrobial outcome. As per the EUCAST guideline of 2019, we calculate resistance as the portion of R (<code><a href="../reference/portion.html">portion_R()</a></code>) and susceptibility as the portion of S and I (<code><a href="../reference/portion.html">portion_SI()</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" title="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_R</a></span>(AMX)</a>
<a class="sourceLine" id="cb25-2" title="2"><span class="co"># [1] 0.4678297</span></a></code></pre></div>
<a class="sourceLine" id="cb25-2" title="2"><span class="co"># [1] 0.4620488</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" title="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb26-2" title="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>
@ -997,19 +1004,19 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4700949</td>
<td align="center">0.4472198</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4625218</td>
<td align="center">0.4684564</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4715272</td>
<td align="center">0.4662494</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4706266</td>
<td align="center">0.4704907</td>
</tr>
</tbody>
</table>
@ -1027,23 +1034,23 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4700949</td>
<td align="center">4531</td>
<td align="center">0.4472198</td>
<td align="center">4604</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4625218</td>
<td align="center">5163</td>
<td align="center">0.4684564</td>
<td align="center">5215</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4715272</td>
<td align="center">2318</td>
<td align="center">0.4662494</td>
<td align="center">2237</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4706266</td>
<td align="center">3064</td>
<td align="center">0.4704907</td>
<td align="center">3016</td>
</tr>
</tbody>
</table>
@ -1063,27 +1070,27 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Escherichia</td>
<td align="center">0.9297487</td>
<td align="center">0.8940827</td>
<td align="center">0.9944610</td>
<td align="center">0.9256476</td>
<td align="center">0.8916924</td>
<td align="center">0.9938263</td>
</tr>
<tr class="even">
<td align="center">Klebsiella</td>
<td align="center">0.8243681</td>
<td align="center">0.9047310</td>
<td align="center">0.9831497</td>
<td align="center">0.8208955</td>
<td align="center">0.8974692</td>
<td align="center">0.9883193</td>
</tr>
<tr class="odd">
<td align="center">Staphylococcus</td>
<td align="center">0.9248778</td>
<td align="center">0.9253923</td>
<td align="center">0.9935683</td>
<td align="center">0.9237813</td>
<td align="center">0.9165096</td>
<td align="center">0.9929976</td>
</tr>
<tr class="even">
<td align="center">Streptococcus</td>
<td align="center">0.6114082</td>
<td align="center">0.6138572</td>
<td align="center">0.0000000</td>
<td align="center">0.6114082</td>
<td align="center">0.6138572</td>
</tr>
</tbody>
</table>

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@ -40,7 +40,7 @@
</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="Released version">0.7.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.7.0.9000</span>
</span>
</div>
@ -199,7 +199,7 @@
<h1>How to apply EUCAST rules</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">03 June 2019</h4>
<h4 class="date">07 June 2019</h4>
<div class="hidden name"><code>EUCAST.Rmd</code></div>

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</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="Released version">0.7.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.7.0.9000</span>
</span>
</div>
@ -199,7 +199,7 @@
<h1>How to determine multi-drug resistance (MDR)</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">03 June 2019</h4>
<h4 class="date">07 June 2019</h4>
<div class="hidden name"><code>MDR.Rmd</code></div>
@ -242,18 +242,18 @@
<p>The data set looks like this now:</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" title="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/head">head</a></span>(my_TB_data)</a>
<a class="sourceLine" id="cb3-2" title="2"><span class="co"># rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin</span></a>
<a class="sourceLine" id="cb3-3" title="3"><span class="co"># 1 S S S R I S</span></a>
<a class="sourceLine" id="cb3-4" title="4"><span class="co"># 2 R R R I R S</span></a>
<a class="sourceLine" id="cb3-5" title="5"><span class="co"># 3 R S S S S I</span></a>
<a class="sourceLine" id="cb3-6" title="6"><span class="co"># 4 S R S R S S</span></a>
<a class="sourceLine" id="cb3-7" title="7"><span class="co"># 5 R S S S S R</span></a>
<a class="sourceLine" id="cb3-8" title="8"><span class="co"># 6 R S S S R R</span></a>
<a class="sourceLine" id="cb3-3" title="3"><span class="co"># 1 R S R R I R</span></a>
<a class="sourceLine" id="cb3-4" title="4"><span class="co"># 2 I S S I S R</span></a>
<a class="sourceLine" id="cb3-5" title="5"><span class="co"># 3 S R S R I R</span></a>
<a class="sourceLine" id="cb3-6" title="6"><span class="co"># 4 R R R R R R</span></a>
<a class="sourceLine" id="cb3-7" title="7"><span class="co"># 5 S S S S R S</span></a>
<a class="sourceLine" id="cb3-8" title="8"><span class="co"># 6 S I S R R I</span></a>
<a class="sourceLine" id="cb3-9" title="9"><span class="co"># kanamycin</span></a>
<a class="sourceLine" id="cb3-10" title="10"><span class="co"># 1 R</span></a>
<a class="sourceLine" id="cb3-11" title="11"><span class="co"># 2 R</span></a>
<a class="sourceLine" id="cb3-12" title="12"><span class="co"># 3 S</span></a>
<a class="sourceLine" id="cb3-13" title="13"><span class="co"># 4 S</span></a>
<a class="sourceLine" id="cb3-14" title="14"><span class="co"># 5 R</span></a>
<a class="sourceLine" id="cb3-10" title="10"><span class="co"># 1 S</span></a>
<a class="sourceLine" id="cb3-11" title="11"><span class="co"># 2 S</span></a>
<a class="sourceLine" id="cb3-12" title="12"><span class="co"># 3 R</span></a>
<a class="sourceLine" id="cb3-13" title="13"><span class="co"># 4 I</span></a>
<a class="sourceLine" id="cb3-14" title="14"><span class="co"># 5 S</span></a>
<a class="sourceLine" id="cb3-15" title="15"><span class="co"># 6 S</span></a></code></pre></div>
<p>We can now add the interpretation of MDR-TB to our data set:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" title="1">my_TB_data<span class="op">$</span>mdr &lt;-<span class="st"> </span><span class="kw"><a href="../reference/mdro.html">mdr_tb</a></span>(my_TB_data)</a>
@ -263,8 +263,7 @@
<a class="sourceLine" id="cb4-5" title="5"><span class="co"># Version: WHO/HTM/TB/2014.11</span></a>
<a class="sourceLine" id="cb4-6" title="6"><span class="co"># Author: WHO (World Health Organization)</span></a>
<a class="sourceLine" id="cb4-7" title="7"><span class="co"># Source: https://www.who.int/tb/publications/pmdt_companionhandbook/en/</span></a>
<a class="sourceLine" id="cb4-8" title="8"><span class="co"># Warning: Reliability might be improved if these antimicrobial results would</span></a>
<a class="sourceLine" id="cb4-9" title="9"><span class="co"># be available too: CAP (capreomycin), RIB (rifabutin), RFP (rifapentine)</span></a></code></pre></div>
<a class="sourceLine" id="cb4-8" title="8"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Reliability might be improved if these antimicrobial results would be available too: CAP (capreomycin), RIB (rifabutin), RFP (rifapentine)</span></a></code></pre></div>
<p>And review the result with a frequency table:</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" title="1"><span class="kw"><a href="../reference/freq.html">freq</a></span>(my_TB_data<span class="op">$</span>mdr)</a></code></pre></div>
<p><strong>Frequency table of <code>mdr</code> from <code>my_TB_data</code> (5,000 x 8)</strong></p>
@ -285,40 +284,40 @@ Unique: 5</p>
<tr class="odd">
<td align="left">1</td>
<td align="left">Mono-resistance</td>
<td align="right">3,238</td>
<td align="right">64.8%</td>
<td align="right">3,238</td>
<td align="right">64.8%</td>
<td align="right">3,283</td>
<td align="right">65.7%</td>
<td align="right">3,283</td>
<td align="right">65.7%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Negative</td>
<td align="right">662</td>
<td align="right">13.2%</td>
<td align="right">3,900</td>
<td align="right">78.0%</td>
<td align="right">650</td>
<td align="right">13.0%</td>
<td align="right">3,933</td>
<td align="right">78.7%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Multidrug resistance</td>
<td align="right">613</td>
<td align="right">12.3%</td>
<td align="right">4,513</td>
<td align="right">90.3%</td>
<td align="right">593</td>
<td align="right">11.9%</td>
<td align="right">4,526</td>
<td align="right">90.5%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Poly-resistance</td>
<td align="right">279</td>
<td align="right">5.6%</td>
<td align="right">4,792</td>
<td align="right">95.8%</td>
<td align="right">259</td>
<td align="right">5.2%</td>
<td align="right">4,785</td>
<td align="right">95.7%</td>
</tr>
<tr class="odd">
<td align="left">5</td>
<td align="left">Extensive drug resistance</td>
<td align="right">208</td>
<td align="right">4.2%</td>
<td align="right">215</td>
<td align="right">4.3%</td>
<td align="right">5,000</td>
<td align="right">100.0%</td>
</tr>

4
docs/articles/SPSS.html
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</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="Released version">0.7.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.7.0.9000</span>
</span>
</div>
@ -199,7 +199,7 @@
<h1>How to import data from SPSS / SAS / Stata</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">03 June 2019</h4>
<h4 class="date">07 June 2019</h4>
<div class="hidden name"><code>SPSS.Rmd</code></div>

6
docs/articles/WHONET.html
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@ -199,7 +199,7 @@
<h1>How to work with WHONET data</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">03 June 2019</h4>
<h4 class="date">07 June 2019</h4>
<div class="hidden name"><code>WHONET.Rmd</code></div>
@ -238,7 +238,7 @@
<p>No errors or warnings, so all values are transformed succesfully. Let’s check it though, with a couple of frequency tables:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" title="1"><span class="co"># our newly created `mo` variable</span></a>
<a class="sourceLine" id="cb4-2" title="2">data <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(mo, <span class="dt">nmax =</span> <span class="dv">10</span>)</a></code></pre></div>
<p><strong>Frequency table of <code>mo</code> from a <code>data.frame</code> (500 x 54)</strong></p>
<p><strong>Frequency table of <code>mo</code> from <code>data</code> (500 x 54)</strong></p>
<p>Class: mo (character)<br>
Length: 500 (of which NA: 0 = 0.00%)<br>
Unique: 39</p>
@ -342,7 +342,7 @@ Species: 38</p>
<a class="sourceLine" id="cb5-2" title="2"><span class="co"># our transformed antibiotic columns</span></a>
<a class="sourceLine" id="cb5-3" title="3"><span class="co"># amoxicillin/clavulanic acid (J01CR02) as an example</span></a>
<a class="sourceLine" id="cb5-4" title="4">data <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(AMC_ND2)</a></code></pre></div>
<p><strong>Frequency table of <code>AMC_ND2</code> from a <code>data.frame</code> (500 x 54)</strong></p>
<p><strong>Frequency table of <code>AMC_ND2</code> from <code>data</code> (500 x 54)</strong></p>
<p>Class: factor &gt; ordered &gt; rsi (numeric)<br>
Length: 500 (of which NA: 19 = 3.80%)<br>
Levels: 3: S &lt; I &lt; R<br>

4
docs/articles/ab_property.html
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@ -40,7 +40,7 @@
</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="Released version">0.7.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.7.0.9000</span>
</span>
</div>
@ -199,7 +199,7 @@
<h1>How to get properties of an antibiotic</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">03 June 2019</h4>
<h4 class="date">07 June 2019</h4>
<div class="hidden name"><code>ab_property.Rmd</code></div>

76
docs/articles/benchmarks.html
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@ -40,7 +40,7 @@
</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="Released version">0.7.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.7.0.9000</span>
</span>
</div>
@ -199,7 +199,7 @@
<h1>Benchmarks</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">03 June 2019</h4>
<h4 class="date">07 June 2019</h4>
<div class="hidden name"><code>benchmarks.Rmd</code></div>
@ -224,14 +224,14 @@
<a class="sourceLine" id="cb2-8" title="8"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb2-9" title="9"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(S.aureus, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">2</span>)</a>
<a class="sourceLine" id="cb2-10" title="10"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb2-11" title="11"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb2-12" title="12"><span class="co"># as.mo("sau") 18 18 22.0 18.0 18.0 62 10</span></a>
<a class="sourceLine" id="cb2-13" title="13"><span class="co"># as.mo("stau") 48 48 53.0 48.0 48.0 93 10</span></a>
<a class="sourceLine" id="cb2-14" title="14"><span class="co"># as.mo("staaur") 17 18 22.0 18.0 18.0 62 10</span></a>
<a class="sourceLine" id="cb2-15" title="15"><span class="co"># as.mo("STAAUR") 18 18 22.0 18.0 18.0 62 10</span></a>
<a class="sourceLine" id="cb2-16" title="16"><span class="co"># as.mo("S. aureus") 28 28 29.0 28.0 29.0 29 10</span></a>
<a class="sourceLine" id="cb2-17" title="17"><span class="co"># as.mo("S. aureus") 28 28 57.0 51.0 73.0 130 10</span></a>
<a class="sourceLine" id="cb2-18" title="18"><span class="co"># as.mo("Staphylococcus aureus") 8 8 9.3 8.1 8.3 20 10</span></a></code></pre></div>
<a class="sourceLine" id="cb2-11" title="11"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb2-12" title="12"><span class="co"># as.mo("sau") 18 18.0 18 18.0 18.0 19 10</span></a>
<a class="sourceLine" id="cb2-13" title="13"><span class="co"># as.mo("stau") 41 41.0 50 42.0 43.0 86 10</span></a>
<a class="sourceLine" id="cb2-14" title="14"><span class="co"># as.mo("staaur") 18 18.0 22 18.0 18.0 64 10</span></a>
<a class="sourceLine" id="cb2-15" title="15"><span class="co"># as.mo("STAAUR") 18 18.0 40 19.0 63.0 97 10</span></a>
<a class="sourceLine" id="cb2-16" title="16"><span class="co"># as.mo("S. aureus") 28 28.0 33 28.0 29.0 73 10</span></a>
<a class="sourceLine" id="cb2-17" title="17"><span class="co"># as.mo("S. aureus") 28 28.0 37 28.0 28.0 120 10</span></a>
<a class="sourceLine" id="cb2-18" title="18"><span class="co"># as.mo("Staphylococcus aureus") 8 8.1 13 8.1 8.3 53 10</span></a></code></pre></div>
<p>In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 5 milliseconds means it can determine 200 input values per second. It case of 100 milliseconds, this is only 10 input values per second. The second input is the only one that has to be looked up thoroughly. All the others are known codes (the first one is a WHONET code) or common laboratory codes, or common full organism names like the last one. Full organism names are always preferred.</p>
<p>To achieve this speed, the <code>as.mo</code> function also takes into account the prevalence of human pathogenic microorganisms. The downside is of course that less prevalent microorganisms will be determined less fast. See this example for the ID of <em>Thermus islandicus</em> (<code>B_THERMS_ISL</code>), a bug probably never found before in humans:</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" title="1">T.islandicus &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"theisl"</span>),</a>
@ -243,12 +243,12 @@
<a class="sourceLine" id="cb3-7" title="7"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(T.islandicus, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">2</span>)</a>
<a class="sourceLine" id="cb3-8" title="8"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb3-9" title="9"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb3-10" title="10"><span class="co"># as.mo("theisl") 470 470 500 510 520 530 10</span></a>
<a class="sourceLine" id="cb3-11" title="11"><span class="co"># as.mo("THEISL") 470 470 480 470 510 520 10</span></a>
<a class="sourceLine" id="cb3-12" title="12"><span class="co"># as.mo("T. islandicus") 74 75 84 75 77 120 10</span></a>
<a class="sourceLine" id="cb3-13" title="13"><span class="co"># as.mo("T. islandicus") 74 74 93 74 120 120 10</span></a>
<a class="sourceLine" id="cb3-14" title="14"><span class="co"># as.mo("Thermus islandicus") 72 73 84 74 77 120 10</span></a></code></pre></div>
<p>That takes 8.1 times as much time on average. A value of 100 milliseconds means it can only determine ~10 different input values per second. We can conclude that looking up arbitrary codes of less prevalent microorganisms is the worst way to go, in terms of calculation performance. Full names (like <em>Thermus islandicus</em>) are almost fast - these are the most probable input from most data sets.</p>
<a class="sourceLine" id="cb3-10" title="10"><span class="co"># as.mo("theisl") 370 370 390 370 420 420 10</span></a>
<a class="sourceLine" id="cb3-11" title="11"><span class="co"># as.mo("THEISL") 370 420 420 420 420 440 10</span></a>
<a class="sourceLine" id="cb3-12" title="12"><span class="co"># as.mo("T. islandicus") 190 190 200 190 230 250 10</span></a>
<a class="sourceLine" id="cb3-13" title="13"><span class="co"># as.mo("T. islandicus") 190 190 210 210 230 240 10</span></a>
<a class="sourceLine" id="cb3-14" title="14"><span class="co"># as.mo("Thermus islandicus") 73 73 83 74 74 120 10</span></a></code></pre></div>
<p>That takes 8.6 times as much time on average. A value of 100 milliseconds means it can only determine ~10 different input values per second. We can conclude that looking up arbitrary codes of less prevalent microorganisms is the worst way to go, in terms of calculation performance. Full names (like <em>Thermus islandicus</em>) are almost fast - these are the most probable input from most data sets.</p>
<p>In the figure below, we compare <em>Escherichia coli</em> (which is very common) with <em>Prevotella brevis</em> (which is moderately common) and with <em>Thermus islandicus</em> (which is very uncommon):</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" title="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/par">par</a></span>(<span class="dt">mar =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="dv">5</span>, <span class="dv">16</span>, <span class="dv">4</span>, <span class="dv">2</span>)) <span class="co"># set more space for left margin text (16)</span></a>
<a class="sourceLine" id="cb4-2" title="2"></a>
@ -294,8 +294,8 @@
<a class="sourceLine" id="cb5-24" title="24"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb5-25" title="25"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb5-26" title="26"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb5-27" title="27"><span class="co"># mo_fullname(x) 1120 1150 1210 1190 1220 1430 10</span></a></code></pre></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 1.19 seconds (1194 ms). You only lose time on your unique input values.</p>
<a class="sourceLine" id="cb5-27" title="27"><span class="co"># mo_fullname(x) 1220 1320 1410 1390 1540 1570 10</span></a></code></pre></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 1.39 seconds (1393 ms). You only lose time on your unique input values.</p>
</div>
<div id="precalculated-results" class="section level3">
<h3 class="hasAnchor">
@ -307,11 +307,11 @@
<a class="sourceLine" id="cb6-4" title="4"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb6-5" title="5"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb6-6" title="6"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb6-7" title="7"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb6-8" title="8"><span class="co"># A 13.20 13.4 13.80 13.70 14.20 14.40 10</span></a>
<a class="sourceLine" id="cb6-9" title="9"><span class="co"># B 25.50 25.9 31.00 26.20 27.60 72.30 10</span></a>
<a class="sourceLine" id="cb6-10" title="10"><span class="co"># C 1.78 1.8 1.89 1.84 2.03 2.06 10</span></a></code></pre></div>
<p>So going from <code><a href="../reference/mo_property.html">mo_fullname("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0018 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
<a class="sourceLine" id="cb6-7" title="7"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb6-8" title="8"><span class="co"># A 13.70 13.90 14.40 14.40 14.60 15.30 10</span></a>
<a class="sourceLine" id="cb6-9" title="9"><span class="co"># B 25.60 26.10 26.80 26.80 27.40 28.30 10</span></a>
<a class="sourceLine" id="cb6-10" title="10"><span class="co"># C 1.59 1.78 1.95 1.96 2.06 2.39 10</span></a></code></pre></div>
<p>So going from <code><a href="../reference/mo_property.html">mo_fullname("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.002 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" title="1">run_it &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="dt">A =</span> <span class="kw"><a href="../reference/mo_property.html">mo_species</a></span>(<span class="st">"aureus"</span>),</a>
<a class="sourceLine" id="cb7-2" title="2"> <span class="dt">B =</span> <span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(<span class="st">"Staphylococcus"</span>),</a>
<a class="sourceLine" id="cb7-3" title="3"> <span class="dt">C =</span> <span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"Staphylococcus aureus"</span>),</a>
@ -324,14 +324,14 @@
<a class="sourceLine" id="cb7-10" title="10"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb7-11" title="11"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb7-12" title="12"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb7-13" title="13"><span class="co"># A 0.526 0.606 0.652 0.639 0.721 0.771 10</span></a>
<a class="sourceLine" id="cb7-14" title="14"><span class="co"># B 0.575 0.582 0.665 0.658 0.689 0.898 10</span></a>
<a class="sourceLine" id="cb7-15" title="15"><span class="co"># C 1.820 1.870 1.940 1.950 2.020 2.070 10</span></a>
<a class="sourceLine" id="cb7-16" title="16"><span class="co"># D 0.547 0.596 0.702 0.665 0.850 0.891 10</span></a>
<a class="sourceLine" id="cb7-17" title="17"><span class="co"># E 0.521 0.560 0.624 0.625 0.655 0.843 10</span></a>
<a class="sourceLine" id="cb7-18" title="18"><span class="co"># F 0.487 0.518 0.596 0.559 0.720 0.754 10</span></a>
<a class="sourceLine" id="cb7-19" title="19"><span class="co"># G 0.483 0.573 0.621 0.605 0.667 0.762 10</span></a>
<a class="sourceLine" id="cb7-20" title="20"><span class="co"># H 0.196 0.270 0.304 0.314 0.348 0.418 10</span></a></code></pre></div>
<a class="sourceLine" id="cb7-13" title="13"><span class="co"># A 0.555 0.585 0.666 0.619 0.777 0.788 10</span></a>
<a class="sourceLine" id="cb7-14" title="14"><span class="co"># B 0.574 0.653 0.771 0.740 0.857 1.080 10</span></a>
<a class="sourceLine" id="cb7-15" title="15"><span class="co"># C 1.630 1.790 1.950 1.930 2.120 2.280 10</span></a>
<a class="sourceLine" id="cb7-16" title="16"><span class="co"># D 0.571 0.671 0.726 0.702 0.725 1.090 10</span></a>
<a class="sourceLine" id="cb7-17" title="17"><span class="co"># E 0.528 0.569 0.704 0.762 0.807 0.833 10</span></a>
<a class="sourceLine" id="cb7-18" title="18"><span class="co"># F 0.511 0.556 0.618 0.580 0.694 0.752 10</span></a>
<a class="sourceLine" id="cb7-19" title="19"><span class="co"># G 0.481 0.538 0.649 0.674 0.736 0.791 10</span></a>
<a class="sourceLine" id="cb7-20" title="20"><span class="co"># H 0.213 0.282 0.336 0.298 0.348 0.636 10</span></a></code></pre></div>
<p>Of course, when running <code><a href="../reference/mo_property.html">mo_phylum("Firmicutes")</a></code> the function has zero knowledge about the actual microorganism, namely <em>S. aureus</em>. But since the result would be <code>"Firmicutes"</code> too, there is no point in calculating the result. And because this package ‘knows’ all phyla of all known bacteria (according to the Catalogue of Life), it can just return the initial value immediately.</p>
</div>
<div id="results-in-other-languages" class="section level3">
@ -358,13 +358,13 @@
<a class="sourceLine" id="cb8-18" title="18"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">4</span>)</a>
<a class="sourceLine" id="cb8-19" title="19"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb8-20" title="20"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb8-21" title="21"><span class="co"># en 18.45 18.62 18.93 18.81 19.03 20.02 10</span></a>
<a class="sourceLine" id="cb8-22" title="22"><span class="co"># de 21.13 21.19 21.67 21.26 21.37 25.28 10</span></a>
<a class="sourceLine" id="cb8-23" title="23"><span class="co"># nl 34.19 34.39 34.74 34.55 34.93 35.99 10</span></a>
<a class="sourceLine" id="cb8-24" title="24"><span class="co"># es 20.92 21.03 25.70 21.26 21.47 65.90 10</span></a>
<a class="sourceLine" id="cb8-25" title="25"><span class="co"># it 20.79 20.94 25.96 21.23 21.88 65.69 10</span></a>
<a class="sourceLine" id="cb8-26" title="26"><span class="co"># fr 20.97 21.04 21.30 21.27 21.44 21.86 10</span></a>
<a class="sourceLine" id="cb8-27" title="27"><span class="co"># pt 20.81 20.91 25.66 21.01 21.24 66.88 10</span></a></code></pre></div>
<a class="sourceLine" id="cb8-21" title="21"><span class="co"># en 18.63 19.06 19.30 19.19 19.41 20.33 10</span></a>
<a class="sourceLine" id="cb8-22" title="22"><span class="co"># de 21.18 21.46 21.63 21.54 21.97 22.09 10</span></a>
<a class="sourceLine" id="cb8-23" title="23"><span class="co"># nl 34.84 35.19 40.04 35.54 36.43 80.26 10</span></a>
<a class="sourceLine" id="cb8-24" title="24"><span class="co"># es 21.00 21.17 21.58 21.49 21.62 23.30 10</span></a>
<a class="sourceLine" id="cb8-25" title="25"><span class="co"># it 21.10 21.26 30.82 21.66 22.58 67.88 10</span></a>
<a class="sourceLine" id="cb8-26" title="26"><span class="co"># fr 20.99 21.25 21.88 21.54 22.50 23.15 10</span></a>
<a class="sourceLine" id="cb8-27" title="27"><span class="co"># pt 21.11 21.24 21.59 21.55 21.91 22.34 10</span></a></code></pre></div>
<p>Currently supported are German, Dutch, Spanish, Italian, French and Portuguese.</p>
</div>
</div>

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@ -40,7 +40,7 @@
</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="Released version">0.7.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.7.0.9000</span>
</span>
</div>
@ -199,7 +199,7 @@
<h1>How to create frequency tables</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">03 June 2019</h4>
<h4 class="date">07 June 2019</h4>
<div class="hidden name"><code>freq.Rmd</code></div>
@ -228,7 +228,7 @@
<a class="sourceLine" id="cb1-9" title="9"></a>
<a class="sourceLine" id="cb1-10" title="10"><span class="co"># Probably the fastest and easiest:</span></a>
<a class="sourceLine" id="cb1-11" title="11">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(gender) </a></code></pre></div>
<p><strong>Frequency table of <code>gender</code> from a <code>data.frame</code> (2,000 x 49)</strong></p>
<p><strong>Frequency table of <code>gender</code> from <code>septic_patients</code> (2,000 x 49)</strong></p>
<p>Class: character<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Unique: 2</p>
@ -285,7 +285,7 @@ Longest: 1</p>
<p>So now the <code>genus</code> and <code>species</code> variables are available. A frequency table of these combined variables can be created like this:</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" title="1">my_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb5-2" title="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(genus, species, <span class="dt">nmax =</span> <span class="dv">15</span>)</a></code></pre></div>
<p><strong>Frequency table of <code>genus</code> and <code>species</code> from a <code>data.frame</code> (2,000 x 64)</strong></p>
<p><strong>Frequency table of <code>genus</code> and <code>species</code> from <code>my_patients</code> (2,000 x 64)</strong></p>
<p>Columns: 2<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Unique: 95</p>
@ -515,7 +515,7 @@ Outliers: 15 (unique count: 12)</p>
<p><code>sort.count</code> is <code>TRUE</code> by default. Compare this default behaviour…</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" title="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb7-2" title="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id)</a></code></pre></div>
<p><strong>Frequency table of <code>hospital_id</code> from a <code>data.frame</code> (2,000 x 49)</strong></p>
<p><strong>Frequency table of <code>hospital_id</code> from <code>septic_patients</code> (2,000 x 49)</strong></p>
<p>Class: factor (numeric)<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Levels: 4: A, B, C, D<br>
@ -567,7 +567,7 @@ Unique: 4</p>
<p>… to this, where items are now sorted on factor levels:</p>
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" title="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb8-2" title="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id, <span class="dt">sort.count =</span> <span class="ot">FALSE</span>)</a></code></pre></div>
<p><strong>Frequency table of <code>hospital_id</code> from a <code>data.frame</code> (2,000 x 49)</strong></p>
<p><strong>Frequency table of <code>hospital_id</code> from <code>septic_patients</code> (2,000 x 49)</strong></p>
<p>Class: factor (numeric)<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Levels: 4: A, B, C, D<br>
@ -619,7 +619,7 @@ Unique: 4</p>
<p>All classes will be printed into the header. Variables with the new <code>rsi</code> class of this AMR package are actually ordered factors and have three classes (look at <code>Class</code> in the header):</p>
<div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb9-1" title="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb9-2" title="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(AMX, <span class="dt">header =</span> <span class="ot">TRUE</span>)</a></code></pre></div>
<p><strong>Frequency table of <code>AMX</code> from a <code>data.frame</code> (2,000 x 49)</strong></p>
<p><strong>Frequency table of <code>AMX</code> from <code>septic_patients</code> (2,000 x 49)</strong></p>
<p>Class: factor &gt; ordered &gt; rsi (numeric)<br>
Length: 2,000 (of which NA: 771 = 38.55%)<br>
Levels: 3: S &lt; I &lt; R<br>
@ -670,7 +670,7 @@ Group: Beta-lactams/penicillins<br>
<p>Frequencies of dates will show the oldest and newest date in the data, and the amount of days between them:</p>
<div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb10-1" title="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb10-2" title="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(date, <span class="dt">nmax =</span> <span class="dv">5</span>, <span class="dt">header =</span> <span class="ot">TRUE</span>)</a></code></pre></div>
<p><strong>Frequency table of <code>date</code> from a <code>data.frame</code> (2,000 x 49)</strong></p>
<p><strong>Frequency table of <code>date</code> from <code>septic_patients</code> (2,000 x 49)</strong></p>
<p>Class: Date (numeric)<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Unique: 1,140</p>
@ -752,7 +752,7 @@ Median: 31 July 2009 (47.39%)</p>
<p>With the <code>na.rm</code> parameter you can remove <code>NA</code> values from the frequency table (defaults to <code>TRUE</code>, but the number of <code>NA</code> values will always be shown into the header):</p>
<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb13-1" title="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb13-2" title="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(AMX, <span class="dt">na.rm =</span> <span class="ot">FALSE</span>)</a></code></pre></div>
<p><strong>Frequency table of <code>AMX</code> from a <code>data.frame</code> (2,000 x 49)</strong></p>
<p><strong>Frequency table of <code>AMX</code> from <code>septic_patients</code> (2,000 x 49)</strong></p>
<p>Class: factor &gt; ordered &gt; rsi (numeric)<br>
Length: 2,000 (of which NA: 771 = 38.55%)<br>
Levels: 3: S &lt; I &lt; R<br>
@ -812,7 +812,7 @@ Group: Beta-lactams/penicillins<br>
<p>A frequency table shows row indices. To remove them, use <code>row.names = FALSE</code>:</p>
<div class="sourceCode" id="cb14"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb14-1" title="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb14-2" title="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id, <span class="dt">row.names =</span> <span class="ot">FALSE</span>)</a></code></pre></div>
<p><strong>Frequency table of <code>hospital_id</code> from a <code>data.frame</code> (2,000 x 49)</strong></p>
<p><strong>Frequency table of <code>hospital_id</code> from <code>septic_patients</code> (2,000 x 49)</strong></p>
<p>Class: factor (numeric)<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Levels: 4: A, B, C, D<br>
@ -864,7 +864,7 @@ Unique: 4</p>
<p>The <code>markdown</code> parameter is <code>TRUE</code> at default in non-interactive sessions, like in reports created with R Markdown. This will always print all rows, unless <code>nmax</code> is set. Without markdown (like in regular R), a frequency table would print like:</p>
<div class="sourceCode" id="cb15"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb15-1" title="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb15-2" title="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id, <span class="dt">markdown =</span> <span class="ot">FALSE</span>)</a>
<a class="sourceLine" id="cb15-3" title="3"><span class="co"># Frequency table of `hospital_id` from a data.frame (2,000 x 49) </span></a>
<a class="sourceLine" id="cb15-3" title="3"><span class="co"># Frequency table of `hospital_id` from `septic_patients` (2,000 x 49) </span></a>
<a class="sourceLine" id="cb15-4" title="4"><span class="co"># </span></a>
<a class="sourceLine" id="cb15-5" title="5"><span class="co"># Class: factor (numeric)</span></a>
<a class="sourceLine" id="cb15-6" title="6"><span class="co"># Length: 2,000 (of which NA: 0 = 0.00%)</span></a>

2
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@ -78,7 +78,7 @@
</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="Released version">0.7.0.9000</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.7.0.9001</span>
</span>
</div>

4
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@ -40,7 +40,7 @@
</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="Released version">0.7.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.7.0.9000</span>
</span>
</div>
@ -199,7 +199,7 @@
<h1>How to get properties of a microorganism</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">03 June 2019</h4>
<h4 class="date">07 June 2019</h4>
<div class="hidden name"><code>mo_property.Rmd</code></div>

4
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@ -40,7 +40,7 @@
</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="Released version">0.7.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.7.0.9000</span>
</span>
</div>
@ -199,7 +199,7 @@
<h1>How to predict antimicrobial resistance</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">03 June 2019</h4>
<h4 class="date">07 June 2019</h4>
<div class="hidden name"><code>resistance_predict.Rmd</code></div>