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DESCRIPTION
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Package: AMR
Version: 1.2.0.9029
Date: 2020-07-08
Version: 1.2.0.9030
Date: 2020-07-09
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(role = c("aut", "cre"),

4
NEWS.md
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# AMR 1.2.0.9029
## <small>Last updated: 08-Jul-2020</small>
# AMR 1.2.0.9030
## <small>Last updated: 09-Jul-2020</small>
### New
* Function `ab_from_text()` to retrieve antimicrobial drug names, doses and forms of administration from clinical texts in e.g. health care records, which also corrects for misspelling since it uses `as.ab()` internally

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docs/404.html
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</button>
<span class="navbar-brand">
<a class="navbar-link" href="https://msberends.github.io/AMR/index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

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docs/LICENSE-text.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="Latest development version">1.2.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

564
docs/articles/AMR.html
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@ -20,7 +20,7 @@
<script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
<script src="../extra.js"></script><meta property="og:title" content="How to conduct AMR analysis">
<meta property="og:description" content="AMR">
<meta property="og:image" content="https://msberends.gitlab.io/AMR/logo.svg">
<meta property="og:image" content="https://msberends.github.io/AMR/logo.svg">
<!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
@ -39,7 +39,7 @@
</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">1.2.0.9011</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>
@ -157,8 +157,8 @@
</ul>
<ul class="nav navbar-nav navbar-right">
<li>
<a href="https://gitlab.com/msberends/AMR">
<span class="fab fa fab fa-gitlab"></span>
<a href="https://github.com/msberends/AMR">
<span class="fab fa fab fa-github"></span>
Source Code
</a>
@ -180,22 +180,22 @@
</header><div class="row">
</header><script src="AMR_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row">
<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>How to conduct AMR analysis</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">22 June 2020</h4>
<h4 class="date">09 July 2020</h4>
<small class="dont-index">Source: <a href="https://gitlab.com/msberends/AMR/blob/master/vignettes/AMR.Rmd"><code>vignettes/AMR.Rmd</code></a></small>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/AMR.Rmd"><code>vignettes/AMR.Rmd</code></a></small>
<div class="hidden name"><code>AMR.Rmd</code></div>
</div>
<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 22 June 2020.</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 09 July 2020.</p>
<div id="introduction" class="section level1">
<h1 class="hasAnchor">
<a href="#introduction" class="anchor"></a>Introduction</h1>
@ -226,21 +226,21 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2020-06-22</td>
<td align="center">2020-07-09</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">2020-06-22</td>
<td align="center">2020-07-09</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">2020-06-22</td>
<td align="center">2020-07-09</td>
<td align="center">efgh</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
@ -336,69 +336,69 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2014-04-15</td>
<td align="center">I4</td>
<td align="center">Hospital D</td>
<td align="center">Escherichia coli</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">2011-02-09</td>
<td align="center">D1</td>
<td align="center">2016-01-30</td>
<td align="center">Y5</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">M</td>
</tr>
<tr class="odd">
<td align="center">2013-12-16</td>
<td align="center">K4</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">R</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="even">
<td align="center">2017-08-23</td>
<td align="center">Z9</td>
<td align="center">Hospital B</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">2010-01-14</td>
<td align="center">N4</td>
<td align="center">Hospital A</td>
<td align="center">Staphylococcus aureus</td>
<tr class="even">
<td align="center">2010-11-13</td>
<td align="center">Y1</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">M</td>
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2016-07-21</td>
<td align="center">U10</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">F</td>
</tr>
<tr class="even">
<td align="center">2016-01-31</td>
<td align="center">N1</td>
<td align="center">Hospital D</td>
<td align="center">2013-03-14</td>
<td align="center">Q1</td>
<td align="center">Hospital B</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2013-04-22</td>
<td align="center">O8</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">R</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2017-11-14</td>
<td align="center">J4</td>
<td align="center">Hospital A</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>
</tbody>
@ -432,18 +432,18 @@ Longest: 1</p>
<tr class="odd">
<td align="left">1</td>
<td align="left">M</td>
<td align="right">10,328</td>
<td align="right">51.64%</td>
<td align="right">10,328</td>
<td align="right">51.64%</td>
<td align="right">10,300</td>
<td align="right">51.5%</td>
<td align="right">10,300</td>
<td align="right">51.5%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">F</td>
<td align="right">9,672</td>
<td align="right">48.36%</td>
<td align="right">9,700</td>
<td align="right">48.5%</td>
<td align="right">20,000</td>
<td align="right">100.00%</td>
<td align="right">100.0%</td>
</tr>
</tbody>
</table>
@ -481,7 +481,7 @@ Longest: 1</p>
<span class="co"># NOTE: Using column `bacteria` as input for `col_mo`.</span>
<span class="co"># NOTE: Using column `date` as input for `col_date`.</span>
<span class="co"># NOTE: Using column `patient_id` as input for `col_patient_id`.</span></pre></body></html></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>
<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="cb16"><html><body><pre class="r"><span class="no">data_1st</span> <span class="kw">&lt;-</span> <span class="no">data</span> <span class="kw">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="no">first</span> <span class="kw">==</span> <span class="fl">TRUE</span>)</pre></body></html></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>
@ -491,7 +491,7 @@ Longest: 1</p>
<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 N3, 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 Y2, sorted on date:</p>
<table class="table">
<thead><tr class="header">
<th align="center">isolate</th>
@ -507,19 +507,19 @@ Longest: 1</p>
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-03-10</td>
<td align="center">N3</td>
<td align="center">2010-03-16</td>
<td align="center">Y2</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">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-05-11</td>
<td align="center">N3</td>
<td align="center">2010-08-04</td>
<td align="center">Y2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -529,19 +529,19 @@ Longest: 1</p>
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-05-17</td>
<td align="center">N3</td>
<td align="center">2010-10-06</td>
<td align="center">Y2</td>
<td align="center">B_ESCHR_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">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-05-18</td>
<td align="center">N3</td>
<td align="center">2010-11-11</td>
<td align="center">Y2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
@ -551,43 +551,43 @@ Longest: 1</p>
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2010-07-30</td>
<td align="center">N3</td>
<td align="center">2010-11-23</td>
<td align="center">Y2</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">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2010-09-15</td>
<td align="center">N3</td>
<td align="center">2011-04-01</td>
<td align="center">Y2</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">R</td>
<td align="center">FALSE</td>
<td align="center">R</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2010-10-06</td>
<td align="center">N3</td>
<td align="center">2011-04-27</td>
<td align="center">Y2</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">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2010-11-30</td>
<td align="center">N3</td>
<td align="center">2011-05-27</td>
<td align="center">Y2</td>
<td align="center">B_ESCHR_COLI</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>
@ -595,34 +595,35 @@ Longest: 1</p>
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-01-27</td>
<td align="center">N3</td>
<td align="center">2011-07-05</td>
<td align="center">Y2</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">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-01-30</td>
<td align="center">N3</td>
<td align="center">2011-09-25</td>
<td align="center">Y2</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">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
</tbody>
</table>
<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>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>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="cb18"><html><body><pre class="r"><span class="no">data</span> <span class="kw">&lt;-</span> <span class="no">data</span> <span class="kw">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="kw">keyab</span> <span class="kw">=</span> <span class="fu"><a href="../reference/key_antibiotics.html">key_antibiotics</a></span>(<span class="no">.</span>)) <span class="kw">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="kw">first_weighted</span> <span class="kw">=</span> <span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span>(<span class="no">.</span>))
<span class="co"># NOTE: Using column `bacteria` as input for `col_mo`.</span>
<span class="co"># NOTE: more than one result was found for item 1: amoxicillin/clavulanic acid, azidocillin</span>
<span class="co"># NOTE: Using column `bacteria` as input for `col_mo`.</span>
<span class="co"># NOTE: Using column `date` as input for `col_date`.</span>
<span class="co"># NOTE: Using column `patient_id` as input for `col_patient_id`.</span>
@ -643,35 +644,35 @@ Longest: 1</p>
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-03-10</td>
<td align="center">N3</td>
<td align="center">2010-03-16</td>
<td align="center">Y2</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">R</td>
<td align="center">R</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">2010-05-11</td>
<td align="center">N3</td>
<td align="center">2010-08-04</td>
<td align="center">Y2</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">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-05-17</td>
<td align="center">N3</td>
<td align="center">2010-10-06</td>
<td align="center">Y2</td>
<td align="center">B_ESCHR_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">S</td>
<td align="center">FALSE</td>
@ -679,23 +680,23 @@ Longest: 1</p>
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-05-18</td>
<td align="center">N3</td>
<td align="center">2010-11-11</td>
<td align="center">Y2</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">FALSE</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2010-07-30</td>
<td align="center">N3</td>
<td align="center">2010-11-23</td>
<td align="center">Y2</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">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
@ -703,34 +704,34 @@ Longest: 1</p>
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2010-09-15</td>
<td align="center">N3</td>
<td align="center">2011-04-01</td>
<td align="center">Y2</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">R</td>
<td align="center">FALSE</td>
<td align="center">R</td>
<td align="center">TRUE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2010-10-06</td>
<td align="center">N3</td>
<td align="center">2011-04-27</td>
<td align="center">Y2</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">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2010-11-30</td>
<td align="center">N3</td>
<td align="center">2011-05-27</td>
<td align="center">Y2</td>
<td align="center">B_ESCHR_COLI</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>
@ -739,11 +740,11 @@ Longest: 1</p>
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-01-27</td>
<td align="center">N3</td>
<td align="center">2011-07-05</td>
<td align="center">Y2</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">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
@ -751,29 +752,44 @@ Longest: 1</p>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-01-30</td>
<td align="center">N3</td>
<td align="center">2011-09-25</td>
<td align="center">Y2</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">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
</tbody>
</table>
<p>Instead of 1, now 7 isolates are flagged. In total, 78.7% of all isolates are marked ‘first weighted’ - 50.4% 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 10 isolates are flagged. In total, 78.3% of all isolates are marked ‘first weighted’ - 49.8% 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="cb19"><html><body><pre class="r"><span class="no">data_1st</span> <span class="kw">&lt;-</span> <span class="no">data</span> <span class="kw">%&gt;%</span>
<span class="fu"><a href="../reference/first_isolate.html">filter_first_weighted_isolate</a></span>()</pre></body></html></div>
<p>So we end up with 15,740 isolates for analysis.</p>
<p>So we end up with 15,664 isolates for analysis.</p>
<p>We can remove unneeded columns:</p>
<div class="sourceCode" id="cb20"><html><body><pre class="r"><span class="no">data_1st</span> <span class="kw">&lt;-</span> <span class="no">data_1st</span> <span class="kw">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(-<span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="no">first</span>, <span class="no">keyab</span>))</pre></body></html></div>
<p>Now our data looks like:</p>
<div class="sourceCode" id="cb21"><html><body><pre class="r"><span class="fu"><a href="https://rdrr.io/r/utils/head.html">head</a></span>(<span class="no">data_1st</span>)</pre></body></html></div>
<table class="table">
<colgroup>
<col width="8%">
<col width="8%">
<col width="8%">
<col width="10%">
<col width="3%">
<col width="3%">
<col width="3%">
<col width="3%">
<col width="5%">
<col width="10%">
<col width="11%">
<col width="8%">
<col width="11%">
</colgroup>
<thead><tr class="header">
<th align="center">date</th>
<th align="center">patient_id</th>
@ -791,93 +807,93 @@ Longest: 1</p>
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2014-04-15</td>
<td align="center">I4</td>
<td align="center">Hospital D</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">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">2011-02-09</td>
<td align="center">D1</td>
<td align="center">2016-01-30</td>
<td align="center">Y5</td>
<td align="center">Hospital A</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="odd">
<td align="center">2013-12-16</td>
<td align="center">K4</td>
<td align="center">Hospital C</td>
<td align="center">B_STPHY_AURS</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">Staphylococcus</td>
<td align="center">aureus</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2017-08-23</td>
<td align="center">Z9</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">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 align="center">2010-01-14</td>
<td align="center">N4</td>
<td align="center">Hospital A</td>
<td align="center">B_STPHY_AURS</td>
<tr class="even">
<td align="center">2010-11-13</td>
<td align="center">Y1</td>
<td align="center">Hospital D</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">M</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 align="center">2016-07-21</td>
<td align="center">U10</td>
<td align="center">Hospital B</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">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">2013-03-14</td>
<td align="center">Q1</td>
<td align="center">Hospital B</td>
<td align="center">B_STPHY_AURS</td>
<td align="center">R</td>
<td align="center">R</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">TRUE</td>
</tr>
<tr class="odd">
<td align="center">2013-04-22</td>
<td align="center">O8</td>
<td align="center">Hospital B</td>
<td align="center">B_STPHY_AURS</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="even">
<td align="center">2016-01-31</td>
<td align="center">N1</td>
<td align="center">Hospital D</td>
<td align="center">B_STPHY_AURS</td>
<td align="center">R</td>
<td align="center">2017-11-14</td>
<td align="center">J4</td>
<td align="center">Hospital A</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">S</td>
<td align="center">M</td>
<td align="center">Gram-positive</td>
<td align="center">Staphylococcus</td>
<td align="center">aureus</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td>
<td align="center">TRUE</td>
</tr>
</tbody>
@ -899,8 +915,8 @@ Longest: 1</p>
<div class="sourceCode" id="cb23"><html><body><pre class="r"><span class="no">data_1st</span> <span class="kw">%&gt;%</span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(<span class="no">genus</span>, <span class="no">species</span>)</pre></body></html></div>
<p><strong>Frequency table</strong></p>
<p>Class: character<br>
Length: 15,740<br>
Available: 15,740 (100%, NA: 0 = 0%)<br>
Length: 15,664<br>
Available: 15,664 (100%, NA: 0 = 0%)<br>
Unique: 4</p>
<p>Shortest: 16<br>
Longest: 24</p>
@ -917,33 +933,33 @@ Longest: 24</p>
<tr class="odd">
<td align="left">1</td>
<td align="left">Escherichia coli</td>
<td align="right">7,938</td>
<td align="right">50.43%</td>
<td align="right">7,938</td>
<td align="right">50.43%</td>
<td align="right">7,860</td>
<td align="right">50.18%</td>
<td align="right">7,860</td>
<td align="right">50.18%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Staphylococcus aureus</td>
<td align="right">3,883</td>
<td align="right">24.67%</td>
<td align="right">11,821</td>
<td align="right">75.10%</td>
<td align="right">3,867</td>
<td align="right">24.69%</td>
<td align="right">11,727</td>
<td align="right">74.87%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Streptococcus pneumoniae</td>
<td align="right">2,317</td>
<td align="right">14.72%</td>
<td align="right">14,138</td>
<td align="right">89.82%</td>
<td align="right">2,386</td>
<td align="right">15.23%</td>
<td align="right">14,113</td>
<td align="right">90.10%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Klebsiella pneumoniae</td>
<td align="right">1,602</td>
<td align="right">10.18%</td>
<td align="right">15,740</td>
<td align="right">1,551</td>
<td align="right">9.90%</td>
<td align="right">15,664</td>
<td align="right">100.00%</td>
</tr>
</tbody>
@ -970,50 +986,50 @@ Longest: 24</p>
<tr class="odd">
<td align="center">E. coli</td>
<td align="center">AMX</td>
<td align="center">3808</td>
<td align="center">236</td>
<td align="center">3894</td>
<td align="center">7938</td>
<td align="center">3765</td>
<td align="center">268</td>
<td align="center">3827</td>
<td align="center">7860</td>
</tr>
<tr class="even">
<td align="center">E. coli</td>
<td align="center">AMC</td>
<td align="center">6223</td>
<td align="center">317</td>
<td align="center">1398</td>
<td align="center">7938</td>
<td align="center">6198</td>
<td align="center">319</td>
<td align="center">1343</td>
<td align="center">7860</td>
</tr>
<tr class="odd">
<td align="center">E. coli</td>
<td align="center">CIP</td>
<td align="center">6050</td>
<td align="center">5971</td>
<td align="center">0</td>
<td align="center">1888</td>
<td align="center">7938</td>
<td align="center">1889</td>
<td align="center">7860</td>
</tr>
<tr class="even">
<td align="center">E. coli</td>
<td align="center">GEN</td>
<td align="center">7130</td>
<td align="center">7088</td>
<td align="center">0</td>
<td align="center">808</td>
<td align="center">7938</td>
<td align="center">772</td>
<td align="center">7860</td>
</tr>
<tr class="odd">
<td align="center">K. pneumoniae</td>
<td align="center">AMX</td>
<td align="center">0</td>
<td align="center">0</td>
<td align="center">1602</td>
<td align="center">1602</td>
<td align="center">1551</td>
<td align="center">1551</td>
</tr>
<tr class="even">
<td align="center">K. pneumoniae</td>
<td align="center">AMC</td>
<td align="center">1241</td>
<td align="center">61</td>
<td align="center">300</td>
<td align="center">1602</td>
<td align="center">1209</td>
<td align="center">72</td>
<td align="center">270</td>
<td align="center">1551</td>
</tr>
</tbody>
</table>
@ -1036,34 +1052,34 @@ Longest: 24</p>
<tr class="odd">
<td align="center">E. coli</td>
<td align="center">CIP</td>
<td align="center">6050</td>
<td align="center">5971</td>
<td align="center">0</td>
<td align="center">1888</td>
<td align="center">7938</td>
<td align="center">1889</td>
<td align="center">7860</td>
</tr>
<tr class="even">
<td align="center">K. pneumoniae</td>
<td align="center">CIP</td>
<td align="center">1218</td>
<td align="center">1192</td>
<td align="center">0</td>
<td align="center">384</td>
<td align="center">1602</td>
<td align="center">359</td>
<td align="center">1551</td>
</tr>
<tr class="odd">
<td align="center">S. aureus</td>
<td align="center">CIP</td>
<td align="center">2967</td>
<td align="center">2946</td>
<td align="center">0</td>
<td align="center">916</td>
<td align="center">3883</td>
<td align="center">921</td>
<td align="center">3867</td>
</tr>
<tr class="even">
<td align="center">S. pneumoniae</td>
<td align="center">CIP</td>
<td align="center">1756</td>
<td align="center">1813</td>
<td align="center">0</td>
<td align="center">561</td>
<td align="center">2317</td>
<td align="center">573</td>
<td align="center">2386</td>
</tr>
</tbody>
</table>
@ -1075,7 +1091,7 @@ 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="cb28"><html><body><pre class="r"><span class="no">data_1st</span> <span class="kw">%&gt;%</span> <span class="fu"><a href="../reference/proportion.html">resistance</a></span>(<span class="no">AMX</span>)
<span class="co"># [1] 0.535324</span></pre></body></html></div>
<span class="co"># [1] 0.5335802</span></pre></body></html></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="cb29"><html><body><pre class="r"><span class="no">data_1st</span> <span class="kw">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="no">hospital</span>) <span class="kw">%&gt;%</span>
@ -1089,19 +1105,19 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.5322921</td>
<td align="center">0.5286835</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.5393839</td>
<td align="center">0.5301545</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.5327529</td>
<td align="center">0.5366460</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.5348690</td>
<td align="center">0.5447207</td>
</tr>
</tbody>
</table>
@ -1120,23 +1136,23 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.5322921</td>
<td align="center">4738</td>
<td align="center">0.5286835</td>
<td align="center">4846</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.5393839</td>
<td align="center">5421</td>
<td align="center">0.5301545</td>
<td align="center">5306</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.5327529</td>
<td align="center">2412</td>
<td align="center">0.5366460</td>
<td align="center">2415</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.5348690</td>
<td align="center">3169</td>
<td align="center">0.5447207</td>
<td align="center">3097</td>
</tr>
</tbody>
</table>
@ -1157,27 +1173,27 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Escherichia</td>
<td align="center">0.8238851</td>
<td align="center">0.8982111</td>
<td align="center">0.9840010</td>
<td align="center">0.8291349</td>
<td align="center">0.9017812</td>
<td align="center">0.9870229</td>
</tr>
<tr class="even">
<td align="center">Klebsiella</td>
<td align="center">0.8127341</td>
<td align="center">0.8951311</td>
<td align="center">0.9818976</td>
<td align="center">0.8259188</td>
<td align="center">0.8994197</td>
<td align="center">0.9890393</td>
</tr>
<tr class="odd">
<td align="center">Staphylococcus</td>
<td align="center">0.8246201</td>
<td align="center">0.9260881</td>
<td align="center">0.9863508</td>
<td align="center">0.8233773</td>
<td align="center">0.9229377</td>
<td align="center">0.9847427</td>
</tr>
<tr class="even">
<td align="center">Streptococcus</td>
<td align="center">0.5463962</td>
<td align="center">0.5481978</td>
<td align="center">0.0000000</td>
<td align="center">0.5463962</td>
<td align="center">0.5481978</td>
</tr>
</tbody>
</table>

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<span class="navbar-brand">
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@ -157,8 +157,8 @@
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@ -180,15 +180,15 @@
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<h1 data-toc-skip>How to apply EUCAST rules</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">28 May 2020</h4>
<h4 class="date">09 July 2020</h4>
<small class="dont-index">Source: <a href="https://gitlab.com/msberends/AMR/blob/master/vignettes/EUCAST.Rmd"><code>vignettes/EUCAST.Rmd</code></a></small>
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@ -20,7 +20,7 @@
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@ -39,7 +39,7 @@
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@ -157,8 +157,8 @@
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@ -180,15 +180,15 @@
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<h1 data-toc-skip>How to determine multi-drug resistance (MDR)</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">28 May 2020</h4>
<h4 class="date">09 July 2020</h4>
<small class="dont-index">Source: <a href="https://gitlab.com/msberends/AMR/blob/master/vignettes/MDR.Rmd"><code>vignettes/MDR.Rmd</code></a></small>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/MDR.Rmd"><code>vignettes/MDR.Rmd</code></a></small>
<div class="hidden name"><code>MDR.Rmd</code></div>
</div>
@ -209,16 +209,20 @@
<ul>
<li>
<p><code>guideline = "CMI2012"</code> (default)</p>
Magiorakos AP, Srinivasan A <em>et al.</em> “Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance.” Clinical Microbiology and Infection (2012) (<a href="https://www.clinicalmicrobiologyandinfection.com/article/S1198-743X(14)61632-3/fulltext">link</a>)</li>
<p>Magiorakos AP, Srinivasan A <em>et al.</em> “Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance.” Clinical Microbiology and Infection (2012) (<a href="https://www.clinicalmicrobiologyandinfection.com/article/S1198-743X(14)61632-3/fulltext">link</a>)</p>
</li>
<li>
<p><code>guideline = "EUCAST"</code></p>
The European international guideline - EUCAST Expert Rules Version 3.1 “Intrinsic Resistance and Exceptional Phenotypes Tables” (<a href="http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf">link</a>)</li>
<p>The European international guideline - EUCAST Expert Rules Version 3.1 “Intrinsic Resistance and Exceptional Phenotypes Tables” (<a href="http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf">link</a>)</p>
</li>
<li>
<p><code>guideline = "TB"</code></p>
The international guideline for multi-drug resistant tuberculosis - World Health Organization “Companion handbook to the WHO guidelines for the programmatic management of drug-resistant tuberculosis” (<a href="https://www.who.int/tb/publications/pmdt_companionhandbook/en/">link</a>)</li>
<p>The international guideline for multi-drug resistant tuberculosis - World Health Organization “Companion handbook to the WHO guidelines for the programmatic management of drug-resistant tuberculosis” (<a href="https://www.who.int/tb/publications/pmdt_companionhandbook/en/">link</a>)</p>
</li>
<li>
<p><code>guideline = "MRGN"</code></p>
The German national guideline - Mueller et al. (2015) Antimicrobial Resistance and Infection Control 4:7. (<a href="https://doi.org/10.1186/s13756-015-0047-6">link</a>)</li>
<p>The German national guideline - Mueller et al. (2015) Antimicrobial Resistance and Infection Control 4:7. (<a href="https://doi.org/10.1186/s13756-015-0047-6">link</a>)</p>
</li>
<li>
<p><code>guideline = "BRMO"</code></p>
<p>The Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu “WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) [ZKH]” (<a href="https://www.rivm.nl/Documenten_en_publicaties/Professioneel_Praktisch/Richtlijnen/Infectieziekten/WIP_Richtlijnen/WIP_Richtlijnen/Ziekenhuizen/WIP_richtlijn_BRMO_Bijzonder_Resistente_Micro_Organismen_ZKH">link</a>)</p>
@ -278,7 +282,7 @@ Unique: 2</p>
<div class="sourceCode" id="cb3"><html><body><pre class="r"><span class="co"># a helper function to get a random vector with values S, I and R</span>
<span class="co"># with the probabilities 50% - 10% - 40%</span>
<span class="no">sample_rsi</span> <span class="kw">&lt;-</span> <span class="kw">function</span>() {
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample</a></span>(<span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"S"</span>, <span class="st">"I"</span>, <span class="st">"R"</span>),
<span class="fu"><a href="https://rdrr.io/r/base/sample.html">sample</a></span>(<span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"S"</span>, <span class="st">"I"</span>, <span class="st">"R"</span>),
<span class="kw">size</span> <span class="kw">=</span> <span class="fl">5000</span>,
<span class="kw">prob</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="fl">0.5</span>, <span class="fl">0.1</span>, <span class="fl">0.4</span>),
<span class="kw">replace</span> <span class="kw">=</span> <span class="fl">TRUE</span>)
@ -302,15 +306,15 @@ Unique: 2</p>
<p>The data set now looks like this:</p>
<div class="sourceCode" id="cb5"><html><body><pre class="r"><span class="fu"><a href="https://rdrr.io/r/utils/head.html">head</a></span>(<span class="no">my_TB_data</span>)
<span class="co"># rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin</span>
<span class="co"># 1 S R R S R R</span>
<span class="co"># 2 R S R S R S</span>
<span class="co"># 3 R R S S R S</span>
<span class="co"># 4 S S S S R S</span>
<span class="co"># 5 S R S S R S</span>
<span class="co"># 6 R S R S S S</span>
<span class="co"># 1 S R R S S I</span>
<span class="co"># 2 S R S S S S</span>
<span class="co"># 3 S S S S S S</span>
<span class="co"># 4 S R S S S R</span>
<span class="co"># 5 R S S S R R</span>
<span class="co"># 6 S R I R R S</span>
<span class="co"># kanamycin</span>
<span class="co"># 1 R</span>
<span class="co"># 2 I</span>
<span class="co"># 1 S</span>
<span class="co"># 2 R</span>
<span class="co"># 3 R</span>
<span class="co"># 4 S</span>
<span class="co"># 5 R</span>
@ -343,40 +347,40 @@ Unique: 5</p>
<tr class="odd">
<td align="left">1</td>
<td align="left">Mono-resistant</td>
<td align="right">3245</td>
<td align="right">64.90%</td>
<td align="right">3245</td>
<td align="right">64.90%</td>
<td align="right">3300</td>
<td align="right">66.00%</td>
<td align="right">3300</td>
<td align="right">66.00%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Negative</td>
<td align="right">678</td>
<td align="right">13.56%</td>
<td align="right">3923</td>
<td align="right">78.46%</td>
<td align="right">636</td>
<td align="right">12.72%</td>
<td align="right">3936</td>
<td align="right">78.72%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Multi-drug-resistant</td>
<td align="right">607</td>
<td align="right">12.14%</td>
<td align="right">4530</td>
<td align="right">90.60%</td>
<td align="right">561</td>
<td align="right">11.22%</td>
<td align="right">4497</td>
<td align="right">89.94%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Poly-resistant</td>
<td align="right">262</td>
<td align="right">5.24%</td>
<td align="right">4792</td>
<td align="right">95.84%</td>
<td align="right">310</td>
<td align="right">6.20%</td>
<td align="right">4807</td>
<td align="right">96.14%</td>
</tr>
<tr class="odd">
<td align="left">5</td>
<td align="left">Extensively drug-resistant</td>
<td align="right">208</td>
<td align="right">4.16%</td>
<td align="right">193</td>
<td align="right">3.86%</td>
<td align="right">5000</td>
<td align="right">100.00%</td>
</tr>

15
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@ -20,7 +20,7 @@
<script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
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@ -39,7 +39,7 @@
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<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
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@ -157,8 +157,8 @@
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@ -180,15 +180,15 @@
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<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>How to conduct principal component analysis (PCA) for AMR</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">28 May 2020</h4>
<h4 class="date">09 July 2020</h4>
<small class="dont-index">Source: <a href="https://gitlab.com/msberends/AMR/blob/master/vignettes/PCA.Rmd"><code>vignettes/PCA.Rmd</code></a></small>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/PCA.Rmd"><code>vignettes/PCA.Rmd</code></a></small>
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@ -39,7 +39,7 @@
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<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
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</span>
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@ -186,7 +186,7 @@
<h1 data-toc-skip>How to import data from SPSS / SAS / Stata</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">08 July 2020</h4>
<h4 class="date">09 July 2020</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/SPSS.Rmd"><code>vignettes/SPSS.Rmd</code></a></small>
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@ -20,7 +20,7 @@
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@ -39,7 +39,7 @@
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
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@ -157,8 +157,8 @@
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@ -180,15 +180,15 @@
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<h1 data-toc-skip>How to work with WHONET data</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">28 May 2020</h4>
<h4 class="date">09 July 2020</h4>
<small class="dont-index">Source: <a href="https://gitlab.com/msberends/AMR/blob/master/vignettes/WHONET.Rmd"><code>vignettes/WHONET.Rmd</code></a></small>
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@ -20,7 +20,7 @@
<script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
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@ -39,7 +39,7 @@
</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">1.2.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
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@ -157,8 +157,8 @@
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@ -180,15 +180,15 @@
</header><div class="row">
</header><script src="benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row">
<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>Benchmarks</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">28 May 2020</h4>
<h4 class="date">09 July 2020</h4>
<small class="dont-index">Source: <a href="https://gitlab.com/msberends/AMR/blob/master/vignettes/benchmarks.Rmd"><code>vignettes/benchmarks.Rmd</code></a></small>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/benchmarks.Rmd"><code>vignettes/benchmarks.Rmd</code></a></small>
<div class="hidden name"><code>benchmarks.Rmd</code></div>
</div>
@ -221,36 +221,21 @@
<span class="kw">times</span> <span class="kw">=</span> <span class="fl">10</span>)
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span>(<span class="no">S.aureus</span>, <span class="kw">unit</span> <span class="kw">=</span> <span class="st">"ms"</span>, <span class="kw">signif</span> <span class="kw">=</span> <span class="fl">2</span>)
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max</span>
<span class="co"># as.mo("sau") 8.5 11.0 17.0 12.0 12.0 43.0</span>
<span class="co"># as.mo("stau") 120.0 130.0 150.0 140.0 160.0 180.0</span>
<span class="co"># as.mo("STAU") 130.0 140.0 150.0 150.0 160.0 170.0</span>
<span class="co"># as.mo("staaur") 7.7 9.1 13.0 11.0 12.0 38.0</span>
<span class="co"># as.mo("STAAUR") 8.3 9.3 15.0 10.0 11.0 37.0</span>
<span class="co"># as.mo("S. aureus") 11.0 12.0 18.0 13.0 14.0 41.0</span>
<span class="co"># as.mo("S aureus") 8.8 11.0 17.0 12.0 13.0 41.0</span>
<span class="co"># as.mo("Staphylococcus aureus") 6.4 6.6 7.4 7.6 7.8 9.1</span>
<span class="co"># as.mo("Staphylococcus aureus (MRSA)") 810.0 870.0 890.0 890.0 900.0 1000.0</span>
<span class="co"># as.mo("Sthafilokkockus aaureuz") 320.0 340.0 370.0 350.0 400.0 490.0</span>
<span class="co"># as.mo("MRSA") 9.2 10.0 13.0 11.0 12.0 37.0</span>
<span class="co"># as.mo("VISA") 12.0 12.0 22.0 13.0 43.0 44.0</span>
<span class="co"># as.mo("VRSA") 11.0 13.0 21.0 14.0 38.0 41.0</span>
<span class="co"># as.mo(22242419) 130.0 140.0 150.0 140.0 170.0 200.0</span>
<span class="co"># neval</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span></pre></body></html></div>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># as.mo("sau") 9.9 14 22 15 36 48 10</span>
<span class="co"># as.mo("stau") 160.0 160 180 170 210 210 10</span>
<span class="co"># as.mo("STAU") 160.0 160 180 170 200 210 10</span>
<span class="co"># as.mo("staaur") 9.5 13 14 14 16 17 10</span>
<span class="co"># as.mo("STAAUR") 9.7 11 13 13 15 19 10</span>
<span class="co"># as.mo("S. aureus") 12.0 13 17 15 18 35 10</span>
<span class="co"># as.mo("S aureus") 11.0 16 26 19 42 43 10</span>
<span class="co"># as.mo("Staphylococcus aureus") 8.7 11 19 13 14 55 10</span>
<span class="co"># as.mo("Staphylococcus aureus (MRSA)") 890.0 910 930 920 950 1000 10</span>
<span class="co"># as.mo("Sthafilokkockus aaureuz") 420.0 430 450 440 470 510 10</span>
<span class="co"># as.mo("MRSA") 9.8 10 13 12 14 19 10</span>
<span class="co"># as.mo("VISA") 12.0 14 33 18 43 120 10</span>
<span class="co"># as.mo("VRSA") 12.0 15 24 17 37 48 10</span>
<span class="co"># as.mo(22242419) 140.0 150 150 150 150 180 10</span></pre></body></html></div>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-4-1.png" width="562.5"></p>
<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.</p>
<p>To achieve this speed, the <code>as.mo</code> function also takes into account the prevalence of human pathogenic microorganisms. The downside of this is of course that less prevalent microorganisms will be determined less fast. See this example for the ID of <em>Methanosarcina semesiae</em> (<code>B_MTHNSR_SEMS</code>), a bug probably never found before in humans:</p>
@ -262,12 +247,12 @@
<span class="kw">times</span> <span class="kw">=</span> <span class="fl">10</span>)
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span>(<span class="no">M.semesiae</span>, <span class="kw">unit</span> <span class="kw">=</span> <span class="st">"ms"</span>, <span class="kw">signif</span> <span class="kw">=</span> <span class="fl">4</span>)
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max</span>
<span class="co"># as.mo("metsem") 143.400 146.300 156.10 155.400 164.900 176.40</span>
<span class="co"># as.mo("METSEM") 141.600 146.900 167.00 170.700 185.000 188.00</span>
<span class="co"># as.mo("M. semesiae") 9.665 9.879 16.50 10.090 11.960 44.29</span>
<span class="co"># as.mo("M. semesiae") 10.000 10.080 14.46 11.660 13.140 42.01</span>
<span class="co"># as.mo("Methanosarcina semesiae") 7.161 7.389 10.40 7.542 9.294 33.00</span>
<span class="co"># expr min lq mean median uq max</span>
<span class="co"># as.mo("metsem") 169.600 189.900 199.30 199.70 211.00 223.90</span>
<span class="co"># as.mo("METSEM") 170.000 186.900 197.40 191.80 210.70 232.30</span>
<span class="co"># as.mo("M. semesiae") 11.330 11.620 12.37 12.21 13.20 13.78</span>
<span class="co"># as.mo("M. semesiae") 11.410 12.090 15.74 12.48 13.55 43.19</span>
<span class="co"># as.mo("Methanosarcina semesiae") 8.592 8.906 12.89 9.31 11.54 41.08</span>
<span class="co"># neval</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
@ -287,11 +272,11 @@
<span class="co"># keep only the unique ones</span>
<span class="fu"><a href="https://rdrr.io/r/base/unique.html">unique</a></span>() <span class="kw">%&gt;%</span>
<span class="co"># pick 50 of them at random</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample</a></span>(<span class="fl">50</span>) <span class="kw">%&gt;%</span>
<span class="fu"><a href="https://rdrr.io/r/base/sample.html">sample</a></span>(<span class="fl">50</span>) <span class="kw">%&gt;%</span>
<span class="co"># paste that 10,000 times</span>
<span class="fu"><a href="https://rdrr.io/r/base/rep.html">rep</a></span>(<span class="fl">10000</span>) <span class="kw">%&gt;%</span>
<span class="co"># scramble it</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample</a></span>()
<span class="fu"><a href="https://rdrr.io/r/base/sample.html">sample</a></span>()
<span class="co"># got indeed 50 times 10,000 = half a million?</span>
<span class="fu"><a href="https://rdrr.io/r/base/length.html">length</a></span>(<span class="no">x</span>)
@ -307,8 +292,8 @@
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span>(<span class="no">run_it</span>, <span class="kw">unit</span> <span class="kw">=</span> <span class="st">"ms"</span>, <span class="kw">signif</span> <span class="kw">=</span> <span class="fl">3</span>)
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># mo_name(x) 1650 1730 1790 1790 1840 1900 10</span></pre></body></html></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 1.79 seconds. You only lose time on your unique input values.</p>
<span class="co"># mo_name(x) 1610 1650 1680 1670 1710 1780 10</span></pre></body></html></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 1.67 seconds. You only lose time on your unique input values.</p>
</div>
<div id="precalculated-results" class="section level3">
<h3 class="hasAnchor">
@ -320,11 +305,11 @@
<span class="kw">times</span> <span class="kw">=</span> <span class="fl">10</span>)
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span>(<span class="no">run_it</span>, <span class="kw">unit</span> <span class="kw">=</span> <span class="st">"ms"</span>, <span class="kw">signif</span> <span class="kw">=</span> <span class="fl">3</span>)
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 5.680 5.820 9.61 6.36 6.850 39.500 10</span>
<span class="co"># B 9.790 10.000 10.60 10.40 10.900 11.900 10</span>
<span class="co"># C 0.229 0.259 0.27 0.27 0.286 0.311 10</span></pre></body></html></div>
<p>So going from <code><a href="../reference/mo_property.html">mo_name("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0003 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>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 8.15 8.69 9.63 9.05 10.40 12.40 10</span>
<span class="co"># B 11.30 12.70 17.50 13.40 14.80 54.30 10</span>
<span class="co"># C 1.04 1.17 1.28 1.28 1.38 1.59 10</span></pre></body></html></div>
<p>So going from <code><a href="../reference/mo_property.html">mo_name("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0013 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="cb6"><html><body><pre class="r"><span class="no">run_it</span> <span class="kw">&lt;-</span> <span class="fu">microbenchmark</span>(<span class="kw">A</span> <span class="kw">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_species</a></span>(<span class="st">"aureus"</span>),
<span class="kw">B</span> <span class="kw">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span>(<span class="st">"Staphylococcus"</span>),
<span class="kw">C</span> <span class="kw">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"Staphylococcus aureus"</span>),
@ -336,15 +321,15 @@
<span class="kw">times</span> <span class="kw">=</span> <span class="fl">10</span>)
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span>(<span class="no">run_it</span>, <span class="kw">unit</span> <span class="kw">=</span> <span class="st">"ms"</span>, <span class="kw">signif</span> <span class="kw">=</span> <span class="fl">3</span>)
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 0.209 0.221 0.236 0.225 0.244 0.311 10</span>
<span class="co"># B 0.197 0.201 0.215 0.212 0.222 0.266 10</span>
<span class="co"># C 0.205 0.224 0.243 0.229 0.242 0.383 10</span>
<span class="co"># D 0.199 0.207 0.216 0.211 0.214 0.270 10</span>
<span class="co"># E 0.196 0.206 0.218 0.215 0.221 0.270 10</span>
<span class="co"># F 0.188 0.197 0.212 0.210 0.216 0.269 10</span>
<span class="co"># G 0.195 0.198 0.213 0.203 0.215 0.299 10</span>
<span class="co"># H 0.184 0.193 0.205 0.201 0.207 0.252 10</span></pre></body></html></div>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 0.852 0.977 1.040 0.990 1.040 1.29 10</span>
<span class="co"># B 0.802 0.933 1.070 0.994 1.160 1.65 10</span>
<span class="co"># C 0.804 0.983 1.060 1.000 1.210 1.32 10</span>
<span class="co"># D 0.783 0.855 0.996 0.989 1.030 1.36 10</span>
<span class="co"># E 0.820 0.962 1.020 0.982 1.070 1.27 10</span>
<span class="co"># F 0.770 0.785 0.937 0.953 0.996 1.30 10</span>
<span class="co"># G 0.963 0.981 1.140 1.160 1.250 1.38 10</span>
<span class="co"># H 0.778 0.842 0.985 0.977 0.995 1.30 10</span></pre></body></html></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> anyway, 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">
@ -370,14 +355,14 @@
<span class="kw">times</span> <span class="kw">=</span> <span class="fl">100</span>)
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span>(<span class="no">run_it</span>, <span class="kw">unit</span> <span class="kw">=</span> <span class="st">"ms"</span>, <span class="kw">signif</span> <span class="kw">=</span> <span class="fl">4</span>)
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># en 9.303 11.59 14.90 12.40 13.63 45.92 100</span>
<span class="co"># de 10.080 12.39 15.77 13.11 14.45 46.27 100</span>
<span class="co"># nl 13.200 16.26 20.88 17.80 19.52 49.93 100</span>
<span class="co"># es 9.957 12.23 15.57 13.12 14.59 51.99 100</span>
<span class="co"># it 10.210 12.44 19.02 13.34 14.74 52.96 100</span>
<span class="co"># fr 10.040 12.40 18.90 13.26 15.07 54.40 100</span>
<span class="co"># pt 10.450 12.67 16.91 13.46 14.68 51.47 100</span></pre></body></html></div>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># en 12.84 13.10 18.11 14.63 15.54 58.10 100</span>
<span class="co"># de 13.58 14.02 18.05 14.61 16.58 69.21 100</span>
<span class="co"># nl 17.07 17.89 22.36 18.97 20.85 68.70 100</span>
<span class="co"># es 13.63 14.20 20.75 15.82 16.79 73.94 100</span>
<span class="co"># it 13.64 13.95 16.95 15.40 16.57 50.96 100</span>
<span class="co"># fr 13.74 14.12 19.84 15.81 16.62 61.13 100</span>
<span class="co"># pt 13.58 14.02 19.00 14.90 16.49 53.41 100</span></pre></body></html></div>
<p>Currently supported are German, Dutch, Spanish, Italian, French and Portuguese.</p>
</div>
</div>

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@ -81,7 +81,7 @@
</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">1.2.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

14
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@ -20,7 +20,7 @@
<script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
<script src="../extra.js"></script><meta property="og:title" content="How to predict antimicrobial resistance">
<meta property="og:description" content="AMR">
<meta property="og:image" content="https://msberends.gitlab.io/AMR/logo.svg">
<meta property="og:image" content="https://msberends.github.io/AMR/logo.svg">
<!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
@ -39,7 +39,7 @@
</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">1.2.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>
@ -157,8 +157,8 @@
</ul>
<ul class="nav navbar-nav navbar-right">
<li>
<a href="https://gitlab.com/msberends/AMR">
<span class="fab fa fab fa-gitlab"></span>
<a href="https://github.com/msberends/AMR">
<span class="fab fa fab fa-github"></span>
Source Code
</a>
@ -180,15 +180,15 @@
</header><div class="row">
</header><script src="resistance_predict_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row">
<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>How to predict antimicrobial resistance</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">28 May 2020</h4>
<h4 class="date">09 July 2020</h4>
<small class="dont-index">Source: <a href="https://gitlab.com/msberends/AMR/blob/master/vignettes/resistance_predict.Rmd"><code>vignettes/resistance_predict.Rmd</code></a></small>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/resistance_predict.Rmd"><code>vignettes/resistance_predict.Rmd</code></a></small>
<div class="hidden name"><code>resistance_predict.Rmd</code></div>
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// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020.
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for (var j = 0; j < linkList.length; j++) {
if (linkList[j].innerHTML === "") {
linkList[j].setAttribute('aria-hidden', 'true');
}
}
}
});

2
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@ -81,7 +81,7 @@
</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">1.2.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

12
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@ -24,10 +24,6 @@
// Add updated Font Awesome 5.8.2 library
$('head').append('<!-- Updated Font Awesome library --><link rel="stylesheet" href="https://use.fontawesome.com/releases/v5.8.2/css/all.css">');
// Email template for new GitLab issues
//https://stackoverflow.com/a/33190494/4575331
//incoming+msberends-amr-9011429-5miwzuo1xo70wbz9r6fwv4dmg-issue@incoming.gitlab.com
$( document ).ready(function() {
// add SurveyMonkey
@ -39,7 +35,7 @@ $( document ).ready(function() {
// remove version label from header
$(".version.label").remove();
// redirect to GitLab
// redirect GitLab to GitHub
var url_old = window.location.href;
var url_new = url_old.replace("gitlab", "github");
if (url_old != url_new) {
@ -57,7 +53,7 @@ $( document ).ready(function() {
' Learn R reading this great book: R for Data Science.' +
' <br><br>' +
' Click to read it online - it was published for free.' +
' <img src="https://gitlab.com/msberends/AMR/raw/master/docs/cover_r4ds.png" height="100px">' +
' <img src="https://github.com/msberends/AMR/raw/master/docs/cover_r4ds.png" height="100px">' +
' </a> ' +
' <hr>' +
'</div>');
@ -67,7 +63,7 @@ $( document ).ready(function() {
$('footer').html(
'<div>' +
'<p><code>AMR</code> (for R). Developed at the <a href="https://www.rug.nl">University of Groningen</a> in collaboration with non-profit organisations <a href="https://www.certe.nl">Certe Medical Diagnostics and Advice</a> and <a href="https://www.umcg.nl">University Medical Center Groningen</a>.</p>' +
'<a href="https://www.rug.nl"><img src="https://gitlab.com/msberends/AMR/raw/master/docs/logo_rug.png" class="footer_logo"></a>' +
'<a href="https://www.rug.nl"><img src="https://github.com/msberends/AMR/raw/master/docs/logo_rug.png" class="footer_logo"></a>' +
'</div>');
// all links should open in new tab/window
$('footer').html($('footer').html().replace(/href/g, 'target="_blank" href'));
@ -101,4 +97,4 @@ $( document ).ready(function() {
$('.template-reference-index h1').text('Manual');
});
$('head').append("<!-- Matomo --><script type='text/javascript'> var _paq = _paq || []; /* tracker methods like 'setCustomDimension' should be called before 'trackPageView' */ _paq.push(['setDomains', ['*.msberends.gitlab.io/AMR']]); _paq.push(['enableCrossDomainLinking']); _paq.push(['trackPageView']); _paq.push(['enableLinkTracking']); (function() { var u='https://analyse.uscloud.nl/'; _paq.push(['setTrackerUrl', u+'piwik.php']); _paq.push(['setSiteId', '3']); var d=document, g=d.createElement('script'), s=d.getElementsByTagName('script')[0]; g.type='text/javascript'; g.async=true; g.defer=true; g.src=u+'piwik.js'; s.parentNode.insertBefore(g,s); })();</script><!-- End Matomo Code -->");
$('head').append("<!-- Global site tag (gtag.js) - Google Analytics --> <script async src=\"https://www.googletagmanager.com/gtag/js?id=UA-172114740-1\"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'UA-172114740-1'); </script><!-- Matomo --><script type='text/javascript'> var _paq = _paq || []; /* tracker methods like 'setCustomDimension' should be called before 'trackPageView' */ _paq.push(['setDomains', ['*.msberends.github.io/AMR']]); _paq.push(['enableCrossDomainLinking']); _paq.push(['trackPageView']); _paq.push(['enableLinkTracking']); (function() { var u='https://analyse.uscloud.nl/'; _paq.push(['setTrackerUrl', u+'piwik.php']); _paq.push(['setSiteId', '3']); var d=document, g=d.createElement('script'), s=d.getElementsByTagName('script')[0]; g.type='text/javascript'; g.async=true; g.defer=true; g.src=u+'piwik.js'; s.parentNode.insertBefore(g,s); })();</script><!-- End Matomo Code -->");

2
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@ -43,7 +43,7 @@
</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">1.2.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

12
docs/news/index.html
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@ -81,7 +81,7 @@
</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">1.2.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>
@ -229,13 +229,13 @@
<small>Source: <a href='https://github.com/msberends/AMR/blob/master/NEWS.md'><code>NEWS.md</code></a></small>
</div>
<div id="amr-1209029" class="section level1">
<h1 class="page-header" data-toc-text="1.2.0.9029">
<a href="#amr-1209029" class="anchor"></a>AMR 1.2.0.9029<small> Unreleased </small>
<div id="amr-1209030" class="section level1">
<h1 class="page-header" data-toc-text="1.2.0.9030">
<a href="#amr-1209030" class="anchor"></a>AMR 1.2.0.9030<small> Unreleased </small>
</h1>
<div id="last-updated-08-jul-2020" class="section level2">
<div id="last-updated-09-jul-2020" class="section level2">
<h2 class="hasAnchor">
<a href="#last-updated-08-jul-2020" class="anchor"></a><small>Last updated: 08-Jul-2020</small>
<a href="#last-updated-09-jul-2020" class="anchor"></a><small>Last updated: 09-Jul-2020</small>
</h2>
<div id="new" class="section level3">
<h3 class="hasAnchor">

2
docs/pkgdown.yml
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@ -10,7 +10,7 @@ articles:
WHONET: WHONET.html
benchmarks: benchmarks.html
resistance_predict: resistance_predict.html
last_built: 2020-07-08T20:53Z
last_built: 2020-07-09T12:07Z
urls:
reference: https://msberends.github.io/AMR/reference
article: https://msberends.github.io/AMR/articles

2
docs/reference/AMR-deprecated.html
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@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/AMR.html
View File

@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/WHOCC.html
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@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/WHONET.html
View File

@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/ab_from_text.html
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@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/ab_property.html
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@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/age.html
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@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/age_groups.html
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@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

10
docs/reference/antibiotic_class_selectors.html
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@ -50,7 +50,7 @@
<meta property="og:title" content="Antibiotic class selectors — antibiotic_class_selectors" />
<meta property="og:description" content="Use these selection helpers inside any function that allows Tidyverse selections, like dplyr::select() or tidyr::pivot_longer(). They help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations." />
<meta property="og:image" content="https://msberends.gitlab.io/AMR/logo.svg" />
<meta property="og:image" content="https://msberends.github.io/AMR/logo.svg" />
@ -82,7 +82,7 @@
</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">1.2.0.9011</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>
@ -200,8 +200,8 @@
</ul>
<ul class="nav navbar-nav navbar-right">
<li>
<a href="https://gitlab.com/msberends/AMR">
<span class="fab fa fab fa-gitlab"></span>
<a href="https://github.com/msberends/AMR">
<span class="fab fa fab fa-github"></span>
Source Code
</a>
@ -227,7 +227,7 @@
<div class="col-md-9 contents">
<div class="page-header">
<h1>Antibiotic class selectors</h1>
<small class="dont-index">Source: <a href='https://gitlab.com/msberends/AMR/blob/master/R/ab_class_selectors.R'><code>R/ab_class_selectors.R</code></a></small>
<small class="dont-index">Source: <a href='https://github.com/msberends/AMR/blob/master/R/ab_class_selectors.R'><code>R/ab_class_selectors.R</code></a></small>
<div class="hidden name"><code>antibiotic_class_selectors.Rd</code></div>
</div>

2
docs/reference/antibiotics.html
View File

@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/as.ab.html
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@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/as.disk.html
View File

@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/as.mic.html
View File

@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/as.mo.html
View File

@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/as.rsi.html
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@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/atc_online.html
View File

@ -83,7 +83,7 @@ This function requires an internet connection." />
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/availability.html
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@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/bug_drug_combinations.html
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@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/catalogue_of_life.html
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@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/catalogue_of_life_version.html
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@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/count.html
View File

@ -83,7 +83,7 @@ count_resistant() should be used to count resistant isolates, count_susceptible(
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/eucast_rules.html
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@ -83,7 +83,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/example_isolates.html
View File

@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/example_isolates_unclean.html
View File

@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/filter_ab_class.html
View File

@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/first_isolate.html
View File

@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/g.test.html
View File

@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/ggplot_pca.html
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@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/ggplot_rsi.html
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@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/guess_ab_col.html
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@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/index.html
View File

@ -81,7 +81,7 @@
</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">1.2.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
</span>
</div>

2
docs/reference/join.html
View File

@ -82,7 +82,7 @@
</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">1.2.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.2.0.9030</span>
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<h1 data-toc-skip>How to apply EUCAST rules</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">28 May 2020</h4>
<small class="dont-index">Source: <a href="https://gitlab.com/msberends/AMR/blob/master/vignettes/EUCAST.Rmd"><code>vignettes/EUCAST.Rmd</code></a></small>
<div class="hidden name"><code>EUCAST.Rmd</code></div>
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<div id="introduction" class="section level2">
<h2 class="hasAnchor">
<a href="#introduction" class="anchor"></a>Introduction</h2>
<p>What are EUCAST rules? The European Committee on Antimicrobial Susceptibility Testing (EUCAST) states <a href="http://www.eucast.org/expert_rules_and_intrinsic_resistance/">on their website</a>:</p>
<blockquote>
<p><em>EUCAST expert rules are a tabulated collection of expert knowledge on intrinsic resistances, exceptional resistance phenotypes and interpretive rules that may be applied to antimicrobial susceptibility testing in order to reduce errors and make appropriate recommendations for reporting particular resistances.</em></p>
</blockquote>
<p>In Europe, a lot of medical microbiological laboratories already apply these rules (<a href="https://www.eurosurveillance.org/content/10.2807/1560-7917.ES2015.20.2.21008">Brown <em>et al.</em>, 2015</a>). Our package features their latest insights on intrinsic resistance and exceptional phenotypes (version 10.0, 2020). Moreover, the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function we use for this purpose can also apply additional rules, like forcing <help title="ATC: J01CA01">ampicillin</help> = R in isolates when <help title="ATC: J01CR02">amoxicillin/clavulanic acid</help> = R.</p>
</div>
<div id="examples" class="section level2">
<h2 class="hasAnchor">
<a href="#examples" class="anchor"></a>Examples</h2>
<p>These rules can be used to discard impossible bug-drug combinations in your data. For example, <em>Klebsiella</em> produces beta-lactamase that prevents ampicillin (or amoxicillin) from working against it. In other words, practically every strain of <em>Klebsiella</em> is resistant to ampicillin.</p>
<p>Sometimes, laboratory data can still contain such strains with ampicillin being susceptible to ampicillin. This could be because an antibiogram is available before an identification is available, and the antibiogram is then not re-interpreted based on the identification (namely, <em>Klebsiella</em>). EUCAST expert rules solve this, that can be applied using <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>:</p>
<div class="sourceCode" id="cb1"><html><body><pre class="r"><span class="no">oops</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span>(<span class="kw">mo</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"Klebsiella"</span>,
<span class="st">"Escherichia"</span>),
<span class="kw">ampicillin</span> <span class="kw">=</span> <span class="st">"S"</span>)
<span class="no">oops</span>
<span class="co"># mo ampicillin</span>
<span class="co"># 1 Klebsiella S</span>
<span class="co"># 2 Escherichia S</span>
<span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span>(<span class="no">oops</span>, <span class="kw">info</span> <span class="kw">=</span> <span class="fl">FALSE</span>)
<span class="co"># mo ampicillin</span>
<span class="co"># 1 Klebsiella R</span>
<span class="co"># 2 Escherichia S</span></pre></body></html></div>
<p>EUCAST rules can not only be used for correction, they can also be used for filling in known resistance and susceptibility based on results of other antimicrobials drugs. This process is called <em>interpretive reading</em> and is part of the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function as well:</p>
<div class="sourceCode" id="cb2"><html><body><pre class="r"><span class="no">data</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span>(<span class="kw">mo</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"Staphylococcus aureus"</span>,
<span class="st">"Enterococcus faecalis"</span>,
<span class="st">"Escherichia coli"</span>,
<span class="st">"Klebsiella pneumoniae"</span>,
<span class="st">"Pseudomonas aeruginosa"</span>),
<span class="kw">VAN</span> <span class="kw">=</span> <span class="st">"-"</span>, <span class="co"># Vancomycin</span>
<span class="kw">AMX</span> <span class="kw">=</span> <span class="st">"-"</span>, <span class="co"># Amoxicillin</span>
<span class="kw">COL</span> <span class="kw">=</span> <span class="st">"-"</span>, <span class="co"># Colistin</span>
<span class="kw">CAZ</span> <span class="kw">=</span> <span class="st">"-"</span>, <span class="co"># Ceftazidime</span>
<span class="kw">CXM</span> <span class="kw">=</span> <span class="st">"-"</span>, <span class="co"># Cefuroxime</span>
<span class="kw">PEN</span> <span class="kw">=</span> <span class="st">"S"</span>, <span class="co"># Penicillin G</span>
<span class="kw">FOX</span> <span class="kw">=</span> <span class="st">"S"</span>, <span class="co"># Cefoxitin</span>
<span class="kw">stringsAsFactors</span> <span class="kw">=</span> <span class="fl">FALSE</span>)</pre></body></html></div>
<div class="sourceCode" id="cb3"><html><body><pre class="r"><span class="no">data</span></pre></body></html></div>
<table class="table">
<thead><tr class="header">
<th align="left">mo</th>
<th align="center">VAN</th>
<th align="center">AMX</th>
<th align="center">COL</th>
<th align="center">CAZ</th>
<th align="center">CXM</th>
<th align="center">PEN</th>
<th align="center">FOX</th>
</tr></thead>
<tbody>
<tr class="odd">
<td align="left">Staphylococcus aureus</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
<tr class="even">
<td align="left">Enterococcus faecalis</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
<tr class="odd">
<td align="left">Escherichia coli</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
<tr class="even">
<td align="left">Klebsiella pneumoniae</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
<tr class="odd">
<td align="left">Pseudomonas aeruginosa</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
</tbody>
</table>
<div class="sourceCode" id="cb4"><html><body><pre class="r"><span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span>(<span class="no">data</span>)</pre></body></html></div>
<pre><code># Warning: Not all columns with antimicrobial results are of class &lt;rsi&gt;.
# Transform eligible columns to class &lt;rsi&gt; on beforehand: your_data %&gt;% mutate_if(is.rsi.eligible, as.rsi)</code></pre>
<table class="table">
<thead><tr class="header">
<th align="left">mo</th>
<th align="center">VAN</th>
<th align="center">AMX</th>
<th align="center">COL</th>
<th align="center">CAZ</th>
<th align="center">CXM</th>
<th align="center">PEN</th>
<th align="center">FOX</th>
</tr></thead>
<tbody>
<tr class="odd">
<td align="left">Staphylococcus aureus</td>
<td align="center">-</td>
<td align="center">S</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>
</tr>
<tr class="even">
<td align="left">Enterococcus faecalis</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
</tr>
<tr class="odd">
<td align="left">Escherichia coli</td>
<td align="center">R</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">R</td>
<td align="center">S</td>
</tr>
<tr class="even">
<td align="left">Klebsiella pneumoniae</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">R</td>
<td align="center">S</td>
</tr>
<tr class="odd">
<td align="left">Pseudomonas aeruginosa</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">R</td>
</tr>
</tbody>
</table>
</div>
</div>
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<h1 data-toc-skip>How to determine multi-drug resistance (MDR)</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">28 May 2020</h4>
<small class="dont-index">Source: <a href="https://gitlab.com/msberends/AMR/blob/master/vignettes/MDR.Rmd"><code>vignettes/MDR.Rmd</code></a></small>
<div class="hidden name"><code>MDR.Rmd</code></div>
</div>
<p>With the function <code><a href="../reference/mdro.html">mdro()</a></code>, you can determine which micro-organisms are multi-drug resistant organisms (MDRO).</p>
<div id="type-of-input" class="section level4">
<h4 class="hasAnchor">
<a href="#type-of-input" class="anchor"></a>Type of input</h4>
<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function takes a data set as input, such as a regular <code>data.frame</code>. It tries to automatically determine the right columns for info about your isolates, like the name of the species and all columns with results of antimicrobial agents. See the help page for more info about how to set the right settings for your data with the command <code><a href="../reference/mdro.html">?mdro</a></code>.</p>
<p>For WHONET data (and most other data), all settings are automatically set correctly.</p>
</div>
<div id="guidelines" class="section level4">
<h4 class="hasAnchor">
<a href="#guidelines" class="anchor"></a>Guidelines</h4>
<p>The function support multiple guidelines. You can select a guideline with the <code>guideline</code> parameter. Currently supported guidelines are (case-insensitive):</p>
<ul>
<li>
<p><code>guideline = "CMI2012"</code> (default)</p>
Magiorakos AP, Srinivasan A <em>et al.</em> “Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance.” Clinical Microbiology and Infection (2012) (<a href="https://www.clinicalmicrobiologyandinfection.com/article/S1198-743X(14)61632-3/fulltext">link</a>)</li>
<li>
<p><code>guideline = "EUCAST"</code></p>
The European international guideline - EUCAST Expert Rules Version 3.1 “Intrinsic Resistance and Exceptional Phenotypes Tables” (<a href="http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf">link</a>)</li>
<li>
<p><code>guideline = "TB"</code></p>
The international guideline for multi-drug resistant tuberculosis - World Health Organization “Companion handbook to the WHO guidelines for the programmatic management of drug-resistant tuberculosis” (<a href="https://www.who.int/tb/publications/pmdt_companionhandbook/en/">link</a>)</li>
<li>
<p><code>guideline = "MRGN"</code></p>
The German national guideline - Mueller et al. (2015) Antimicrobial Resistance and Infection Control 4:7. (<a href="https://doi.org/10.1186/s13756-015-0047-6">link</a>)</li>
<li>
<p><code>guideline = "BRMO"</code></p>
<p>The Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu “WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) [ZKH]” (<a href="https://www.rivm.nl/Documenten_en_publicaties/Professioneel_Praktisch/Richtlijnen/Infectieziekten/WIP_Richtlijnen/WIP_Richtlijnen/Ziekenhuizen/WIP_richtlijn_BRMO_Bijzonder_Resistente_Micro_Organismen_ZKH">link</a>)</p>
</li>
</ul>
</div>
<div id="examples" class="section level4">
<h4 class="hasAnchor">
<a href="#examples" class="anchor"></a>Examples</h4>
<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function always returns an ordered <code>factor</code>. For example, the output of the default guideline by Magiorakos <em>et al.</em> returns a <code>factor</code> with levels ‘Negative’, ‘MDR’, ‘XDR’ or ‘PDR’ in that order.</p>
<p>The next example uses the <code>example_isolates</code> data set. This is a data set included with this package and contains 2,000 microbial isolates with their full antibiograms. It reflects reality and can be used to practice AMR analysis. If we test the MDR/XDR/PDR guideline on this data set, we get:</p>
<div class="sourceCode" id="cb1"><html><body><pre class="r"><span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="no">dplyr</span>) <span class="co"># to support pipes: %&gt;%</span>
<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="no">cleaner</span>) <span class="co"># to create frequency tables</span></pre></body></html></div>
<div class="sourceCode" id="cb2"><html><body><pre class="r"><span class="no">example_isolates</span> <span class="kw">%&gt;%</span>
<span class="fu"><a href="../reference/mdro.html">mdro</a></span>() <span class="kw">%&gt;%</span>
<span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>() <span class="co"># show frequency table of the result</span>
<span class="co"># NOTE: Using column `mo` as input for `col_mo`.</span>
<span class="co"># NOTE: Auto-guessing columns suitable for analysis...OK.</span>
<span class="co"># NOTE: Reliability would be improved if these antimicrobial results would be available too: ceftaroline (CPT), fusidic acid (FUS), telavancin (TLV), daptomycin (DAP), quinupristin/dalfopristin (QDA), minocycline (MNO), gentamicin-high (GEH), streptomycin-high (STH), doripenem (DOR), levofloxacin (LVX), netilmicin (NET), ticarcillin/clavulanic acid (TCC), ertapenem (ETP), cefotetan (CTT), aztreonam (ATM), ampicillin/sulbactam (SAM), polymyxin B (PLB)</span>
<span class="co"># Warning in mdro(.): NA introduced for isolates where the available percentage of</span>
<span class="co"># antimicrobial classes was below 50% (set with `pct_required_classes`)</span></pre></body></html></div>
<p><strong>Frequency table</strong></p>
<p>Class: factor &gt; ordered (numeric)<br>
Length: 2,000<br>
Levels: 4: Negative &lt; Multi-drug-resistant (MDR) &lt; Extensively drug-resistant …<br>
Available: 1,711 (85.55%, NA: 289 = 14.45%)<br>
Unique: 2</p>
<table class="table">
<thead><tr class="header">
<th align="left"></th>
<th align="left">Item</th>
<th align="right">Count</th>
<th align="right">Percent</th>
<th align="right">Cum. Count</th>
<th align="right">Cum. Percent</th>
</tr></thead>
<tbody>
<tr class="odd">
<td align="left">1</td>
<td align="left">Negative</td>
<td align="right">1595</td>
<td align="right">93.22%</td>
<td align="right">1595</td>
<td align="right">93.22%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Multi-drug-resistant (MDR)</td>
<td align="right">116</td>
<td align="right">6.78%</td>
<td align="right">1711</td>
<td align="right">100.00%</td>
</tr>
</tbody>
</table>
<p>For another example, I will create a data set to determine multi-drug resistant TB:</p>
<div class="sourceCode" id="cb3"><html><body><pre class="r"><span class="co"># a helper function to get a random vector with values S, I and R</span>
<span class="co"># with the probabilities 50% - 10% - 40%</span>
<span class="no">sample_rsi</span> <span class="kw">&lt;-</span> <span class="kw">function</span>() {
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample</a></span>(<span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"S"</span>, <span class="st">"I"</span>, <span class="st">"R"</span>),
<span class="kw">size</span> <span class="kw">=</span> <span class="fl">5000</span>,
<span class="kw">prob</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="fl">0.5</span>, <span class="fl">0.1</span>, <span class="fl">0.4</span>),
<span class="kw">replace</span> <span class="kw">=</span> <span class="fl">TRUE</span>)
}
<span class="no">my_TB_data</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span>(<span class="kw">rifampicin</span> <span class="kw">=</span> <span class="fu">sample_rsi</span>(),
<span class="kw">isoniazid</span> <span class="kw">=</span> <span class="fu">sample_rsi</span>(),
<span class="kw">gatifloxacin</span> <span class="kw">=</span> <span class="fu">sample_rsi</span>(),
<span class="kw">ethambutol</span> <span class="kw">=</span> <span class="fu">sample_rsi</span>(),
<span class="kw">pyrazinamide</span> <span class="kw">=</span> <span class="fu">sample_rsi</span>(),
<span class="kw">moxifloxacin</span> <span class="kw">=</span> <span class="fu">sample_rsi</span>(),
<span class="kw">kanamycin</span> <span class="kw">=</span> <span class="fu">sample_rsi</span>())</pre></body></html></div>
<p>Because all column names are automatically verified for valid drug names or codes, this would have worked exactly the same:</p>
<div class="sourceCode" id="cb4"><html><body><pre class="r"><span class="no">my_TB_data</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span>(<span class="kw">RIF</span> <span class="kw">=</span> <span class="fu">sample_rsi</span>(),
<span class="kw">INH</span> <span class="kw">=</span> <span class="fu">sample_rsi</span>(),
<span class="kw">GAT</span> <span class="kw">=</span> <span class="fu">sample_rsi</span>(),
<span class="kw">ETH</span> <span class="kw">=</span> <span class="fu">sample_rsi</span>(),
<span class="kw">PZA</span> <span class="kw">=</span> <span class="fu">sample_rsi</span>(),
<span class="kw">MFX</span> <span class="kw">=</span> <span class="fu">sample_rsi</span>(),
<span class="kw">KAN</span> <span class="kw">=</span> <span class="fu">sample_rsi</span>())</pre></body></html></div>
<p>The data set now looks like this:</p>
<div class="sourceCode" id="cb5"><html><body><pre class="r"><span class="fu"><a href="https://rdrr.io/r/utils/head.html">head</a></span>(<span class="no">my_TB_data</span>)
<span class="co"># rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin</span>
<span class="co"># 1 S R R S R R</span>
<span class="co"># 2 R S R S R S</span>
<span class="co"># 3 R R S S R S</span>
<span class="co"># 4 S S S S R S</span>
<span class="co"># 5 S R S S R S</span>
<span class="co"># 6 R S R S S S</span>
<span class="co"># kanamycin</span>
<span class="co"># 1 R</span>
<span class="co"># 2 I</span>
<span class="co"># 3 R</span>
<span class="co"># 4 S</span>
<span class="co"># 5 R</span>
<span class="co"># 6 S</span></pre></body></html></div>
<p>We can now add the interpretation of MDR-TB to our data set. You can use:</p>
<div class="sourceCode" id="cb6"><html><body><pre class="r"><span class="fu"><a href="../reference/mdro.html">mdro</a></span>(<span class="no">my_TB_data</span>, <span class="kw">guideline</span> <span class="kw">=</span> <span class="st">"TB"</span>)</pre></body></html></div>
<p>or its shortcut <code><a href="../reference/mdro.html">mdr_tb()</a></code>:</p>
<div class="sourceCode" id="cb7"><html><body><pre class="r"><span class="no">my_TB_data</span>$<span class="no">mdr</span> <span class="kw">&lt;-</span> <span class="fu"><a href="../reference/mdro.html">mdr_tb</a></span>(<span class="no">my_TB_data</span>)
<span class="co"># NOTE: No column found as input for `col_mo`, assuming all records contain Mycobacterium tuberculosis.</span>
<span class="co"># NOTE: Auto-guessing columns suitable for analysis...OK.</span>
<span class="co"># NOTE: Reliability would be improved if these antimicrobial results would be available too: capreomycin (CAP), rifabutin (RIB), rifapentine (RFP)</span></pre></body></html></div>
<p>Create a frequency table of the results:</p>
<div class="sourceCode" id="cb8"><html><body><pre class="r"><span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(<span class="no">my_TB_data</span>$<span class="no">mdr</span>)</pre></body></html></div>
<p><strong>Frequency table</strong></p>
<p>Class: factor &gt; ordered (numeric)<br>
Length: 5,000<br>
Levels: 5: Negative &lt; Mono-resistant &lt; Poly-resistant &lt; Multi-drug-resistant &lt;…<br>
Available: 5,000 (100%, NA: 0 = 0%)<br>
Unique: 5</p>
<table class="table">
<thead><tr class="header">
<th align="left"></th>
<th align="left">Item</th>
<th align="right">Count</th>
<th align="right">Percent</th>
<th align="right">Cum. Count</th>
<th align="right">Cum. Percent</th>
</tr></thead>
<tbody>
<tr class="odd">
<td align="left">1</td>
<td align="left">Mono-resistant</td>
<td align="right">3245</td>
<td align="right">64.90%</td>
<td align="right">3245</td>
<td align="right">64.90%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Negative</td>
<td align="right">678</td>
<td align="right">13.56%</td>
<td align="right">3923</td>
<td align="right">78.46%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Multi-drug-resistant</td>
<td align="right">607</td>
<td align="right">12.14%</td>
<td align="right">4530</td>
<td align="right">90.60%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Poly-resistant</td>
<td align="right">262</td>
<td align="right">5.24%</td>
<td align="right">4792</td>
<td align="right">95.84%</td>
</tr>
<tr class="odd">
<td align="left">5</td>
<td align="left">Extensively drug-resistant</td>
<td align="right">208</td>
<td align="right">4.16%</td>
<td align="right">5000</td>
<td align="right">100.00%</td>
</tr>
</tbody>
</table>
</div>
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<h1 data-toc-skip>How to conduct principal component analysis (PCA) for AMR</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">28 May 2020</h4>
<small class="dont-index">Source: <a href="https://gitlab.com/msberends/AMR/blob/master/vignettes/PCA.Rmd"><code>vignettes/PCA.Rmd</code></a></small>
<div class="hidden name"><code>PCA.Rmd</code></div>
</div>
<p><strong>NOTE: This page will be updated soon, as the pca() function is currently being developed.</strong></p>
<div id="introduction" class="section level1">
<h1 class="hasAnchor">
<a href="#introduction" class="anchor"></a>Introduction</h1>
</div>
<div id="transforming" class="section level1">
<h1 class="hasAnchor">
<a href="#transforming" class="anchor"></a>Transforming</h1>
<p>For PCA, we need to transform our AMR data first. This is what the <code>example_isolates</code> data set in this package looks like:</p>
<div class="sourceCode" id="cb1"><html><body><pre class="r"><span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="no">AMR</span>)
<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="no">dplyr</span>)
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/reexports.html">glimpse</a></span>(<span class="no">example_isolates</span>)
<span class="co"># Rows: 2,000</span>
<span class="co"># Columns: 49</span>
<span class="co"># $ date &lt;date&gt; 2002-01-02, 2002-01-03, 2002-01-07, 2002-01-07, 2002…</span>
<span class="co"># $ hospital_id &lt;fct&gt; D, D, B, B, B, B, D, D, B, B, D, D, D, D, D, B, B, B,…</span>
<span class="co"># $ ward_icu &lt;lgl&gt; FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, T…</span>
<span class="co"># $ ward_clinical &lt;lgl&gt; TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, F…</span>
<span class="co"># $ ward_outpatient &lt;lgl&gt; FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALS…</span>
<span class="co"># $ age &lt;dbl&gt; 65, 65, 45, 45, 45, 45, 78, 78, 45, 79, 67, 67, 71, 7…</span>
<span class="co"># $ gender &lt;chr&gt; "F", "F", "F", "F", "F", "F", "M", "M", "F", "F", "M"…</span>
<span class="co"># $ patient_id &lt;chr&gt; "A77334", "A77334", "067927", "067927", "067927", "06…</span>
<span class="co"># $ mo &lt;mo&gt; "B_ESCHR_COLI", "B_ESCHR_COLI", "B_STPHY_EPDR", "B_STP…</span>
<span class="co"># $ PEN &lt;ord&gt; R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R,…</span>
<span class="co"># $ OXA &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ FLC &lt;ord&gt; NA, NA, R, R, R, R, S, S, R, S, S, S, NA, NA, NA, NA,…</span>
<span class="co"># $ AMX &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ AMC &lt;ord&gt; I, I, NA, NA, NA, NA, S, S, NA, NA, S, S, I, I, R, I,…</span>
<span class="co"># $ AMP &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ TZP &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ CZO &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ FEP &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ CXM &lt;ord&gt; I, I, R, R, R, R, S, S, R, S, S, S, S, S, NA, S, S, R…</span>
<span class="co"># $ FOX &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ CTX &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S,…</span>
<span class="co"># $ CAZ &lt;ord&gt; NA, NA, R, R, R, R, R, R, R, R, R, R, NA, NA, NA, S, …</span>
<span class="co"># $ CRO &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S,…</span>
<span class="co"># $ GEN &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ TOB &lt;ord&gt; NA, NA, NA, NA, NA, NA, S, S, NA, NA, NA, NA, S, S, N…</span>
<span class="co"># $ AMK &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ KAN &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ TMP &lt;ord&gt; R, R, S, S, R, R, R, R, S, S, NA, NA, S, S, S, S, S, …</span>
<span class="co"># $ SXT &lt;ord&gt; R, R, S, S, NA, NA, NA, NA, S, S, NA, NA, S, S, S, S,…</span>
<span class="co"># $ NIT &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ FOS &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ LNZ &lt;ord&gt; R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R…</span>
<span class="co"># $ CIP &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, NA, NA, NA,…</span>
<span class="co"># $ MFX &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ VAN &lt;ord&gt; R, R, S, S, S, S, S, S, S, S, NA, NA, R, R, R, R, R, …</span>
<span class="co"># $ TEC &lt;ord&gt; R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R…</span>
<span class="co"># $ TCY &lt;ord&gt; R, R, S, S, S, S, S, S, S, I, S, S, NA, NA, I, R, R, …</span>
<span class="co"># $ TGC &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ DOX &lt;ord&gt; NA, NA, S, S, S, S, S, S, S, NA, S, S, NA, NA, NA, R,…</span>
<span class="co"># $ ERY &lt;ord&gt; R, R, R, R, R, R, S, S, R, S, S, S, R, R, R, R, R, R,…</span>
<span class="co"># $ CLI &lt;ord&gt; NA, NA, NA, NA, NA, R, NA, NA, NA, NA, NA, NA, NA, NA…</span>
<span class="co"># $ AZM &lt;ord&gt; R, R, R, R, R, R, S, S, R, S, S, S, R, R, R, R, R, R,…</span>
<span class="co"># $ IPM &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S,…</span>
<span class="co"># $ MEM &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ MTR &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ CHL &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ COL &lt;ord&gt; NA, NA, R, R, R, R, R, R, R, R, R, R, NA, NA, NA, R, …</span>
<span class="co"># $ MUP &lt;ord&gt; NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…</span>
<span class="co"># $ RIF &lt;ord&gt; R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R…</span></pre></body></html></div>
<p>Now to transform this to a data set with only resistance percentages per taxonomic order and genus:</p>
<div class="sourceCode" id="cb2"><html><body><pre class="r"><span class="no">resistance_data</span> <span class="kw">&lt;-</span> <span class="no">example_isolates</span> <span class="kw">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="kw">order</span> <span class="kw">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_order</a></span>(<span class="no">mo</span>), <span class="co"># group on anything, like order</span>
<span class="kw">genus</span> <span class="kw">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span>(<span class="no">mo</span>)) <span class="kw">%&gt;%</span> <span class="co"># and genus as we do here</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise_all.html">summarise_if</a></span>(<span class="no">is.rsi</span>, <span class="no">resistance</span>) <span class="kw">%&gt;%</span> <span class="co"># then get resistance of all drugs</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="no">order</span>, <span class="no">genus</span>, <span class="no">AMC</span>, <span class="no">CXM</span>, <span class="no">CTX</span>,
<span class="no">CAZ</span>, <span class="no">GEN</span>, <span class="no">TOB</span>, <span class="no">TMP</span>, <span class="no">SXT</span>) <span class="co"># and select only relevant columns</span>
<span class="fu"><a href="https://rdrr.io/r/utils/head.html">head</a></span>(<span class="no">resistance_data</span>)
<span class="co"># # A tibble: 6 x 10</span>
<span class="co"># # Groups: order [2]</span>
<span class="co"># order genus AMC CXM CTX CAZ GEN TOB TMP SXT</span>
<span class="co"># &lt;chr&gt; &lt;chr&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt;</span>
<span class="co"># 1 (unknown order) (unknown genu… NA NA NA NA NA NA NA NA</span>
<span class="co"># 2 Actinomycetales Corynebacteri… NA NA NA NA NA NA NA NA</span>
<span class="co"># 3 Actinomycetales Cutibacterium NA NA NA NA NA NA NA NA</span>
<span class="co"># 4 Actinomycetales Dermabacter NA NA NA NA NA NA NA NA</span>
<span class="co"># 5 Actinomycetales Micrococcus NA NA NA NA NA NA NA NA</span>
<span class="co"># 6 Actinomycetales Rothia NA NA NA NA NA NA NA NA</span></pre></body></html></div>
</div>
<div id="perform-principal-component-analysis" class="section level1">
<h1 class="hasAnchor">
<a href="#perform-principal-component-analysis" class="anchor"></a>Perform principal component analysis</h1>
<p>The new <code><a href="../reference/pca.html">pca()</a></code> function will automatically filter on rows that contain numeric values in all selected variables, so we now only need to do:</p>
<div class="sourceCode" id="cb3"><html><body><pre class="r"><span class="no">pca_result</span> <span class="kw">&lt;-</span> <span class="fu"><a href="../reference/pca.html">pca</a></span>(<span class="no">resistance_data</span>)
<span class="co"># NOTE: Columns selected for PCA: AMC CXM CTX CAZ GEN TOB TMP SXT.</span>
<span class="co"># Total observations available: 7.</span></pre></body></html></div>
<p>The result can be reviewed with the good old <code><a href="https://rdrr.io/r/base/summary.html">summary()</a></code> function:</p>
<div class="sourceCode" id="cb4"><html><body><pre class="r"><span class="fu"><a href="https://rdrr.io/r/base/summary.html">summary</a></span>(<span class="no">pca_result</span>)
<span class="co"># Importance of components:</span>
<span class="co"># PC1 PC2 PC3 PC4 PC5 PC6 PC7</span>
<span class="co"># Standard deviation 2.154 1.6809 0.61305 0.33882 0.20755 0.03137 1.602e-16</span>
<span class="co"># Proportion of Variance 0.580 0.3532 0.04698 0.01435 0.00538 0.00012 0.000e+00</span>
<span class="co"># Cumulative Proportion 0.580 0.9332 0.98014 0.99449 0.99988 1.00000 1.000e+00</span></pre></body></html></div>
<p>Good news. The first two components explain a total of 93.3% of the variance (see the PC1 and PC2 values of the <em>Proportion of Variance</em>. We can create a so-called biplot with the base R <code><a href="https://rdrr.io/r/stats/biplot.html">biplot()</a></code> function, to see which antimicrobial resistance per drug explain the difference per microorganism.</p>
</div>
<div id="plotting-the-results" class="section level1">
<h1 class="hasAnchor">
<a href="#plotting-the-results" class="anchor"></a>Plotting the results</h1>
<div class="sourceCode" id="cb5"><html><body><pre class="r"><span class="fu"><a href="https://rdrr.io/r/stats/biplot.html">biplot</a></span>(<span class="no">pca_result</span>)</pre></body></html></div>
<p><img src="PCA_files/figure-html/unnamed-chunk-5-1.png" width="750"></p>
<p>But we can’t see the explanation of the points. Perhaps this works better with our new <code><a href="../reference/ggplot_pca.html">ggplot_pca()</a></code> function, that automatically adds the right labels and even groups:</p>
<div class="sourceCode" id="cb6"><html><body><pre class="r"><span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span>(<span class="no">pca_result</span>)</pre></body></html></div>
<p><img src="PCA_files/figure-html/unnamed-chunk-6-1.png" width="750"></p>
<p>You can also print an ellipse per group, and edit the appearance:</p>
<div class="sourceCode" id="cb7"><html><body><pre class="r"><span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span>(<span class="no">pca_result</span>, <span class="kw">ellipse</span> <span class="kw">=</span> <span class="fl">TRUE</span>) +
<span class="kw pkg">ggplot2</span><span class="kw ns">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html">labs</a></span>(<span class="kw">title</span> <span class="kw">=</span> <span class="st">"An AMR/PCA biplot!"</span>)</pre></body></html></div>
<p><img src="PCA_files/figure-html/unnamed-chunk-7-1.png" width="750"></p>
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<h1 data-toc-skip>How to import data from SPSS / SAS / Stata</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">08 July 2020</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/SPSS.Rmd"><code>vignettes/SPSS.Rmd</code></a></small>
<div class="hidden name"><code>SPSS.Rmd</code></div>
</div>
<div id="spss-sas-stata" class="section level2">
<h2 class="hasAnchor">
<a href="#spss-sas-stata" class="anchor"></a>SPSS / SAS / Stata</h2>
<p>SPSS (Statistical Package for the Social Sciences) is probably the most well-known software package for statistical analysis. SPSS is easier to learn than R, because in SPSS you only have to click a menu to run parts of your analysis. Because of its user-friendliness, it is taught at universities and particularly useful for students who are new to statistics. From my experience, I would guess that pretty much all (bio)medical students know it at the time they graduate. SAS and Stata are comparable statistical packages popular in big industries.</p>
</div>
<div id="compared-to-r" class="section level2">
<h2 class="hasAnchor">
<a href="#compared-to-r" class="anchor"></a>Compared to R</h2>
<p>As said, SPSS is easier to learn than R. But SPSS, SAS and Stata come with major downsides when comparing it with R:</p>
<ul>
<li>
<p><strong>R is highly modular.</strong></p>
<p>The <a href="https://cran.r-project.org/">official R network (CRAN)</a> features almost 14,000 packages at the time of writing, our <code>AMR</code> package being one of them. All these packages were peer-reviewed before publication. Aside from this official channel, there are also developers who choose not to submit to CRAN, but rather keep it on their own public repository, like GitHub. So there may even be a lot more than 14,000 packages out there.</p>
<p>Bottom line is, you can really extend it yourself or ask somebody to do this for you. Take for example our <code>AMR</code> package. Among other things, it adds reliable reference data to R to help you with the data cleaning and analysis. SPSS, SAS and Stata will never know what a valid MIC value is or what the Gram stain of <em>E. coli</em> is. Or that all species of <em>Klebiella</em> are resistant to amoxicillin and that Floxapen<sup>®</sup> is a trade name of flucloxacillin. These facts and properties are often needed to clean existing data, which would be very inconvenient in a software package without reliable reference data. See below for a demonstration.</p>
</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, 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>
<p>Over the last years, <a href="https://rmarkdown.rstudio.com/">R Markdown</a> has really made an interesting development. With R Markdown, you can very easily produce reports, whether the format has to be Word, PowerPoint, a website, a PDF document or just the raw data to Excel. It even allows the use of a reference file containing the layout style (e.g. fonts and colours) of your organisation. I use this a lot to generate weekly and monthly reports automatically. Just write the code once and enjoy the automatically updated reports at any interval you like.</p>
<p>For an even more professional environment, you could create <a href="https://shiny.rstudio.com/">Shiny apps</a>: live manipulation of data using a custom made website. The webdesign knowledge needed (JavaScript, CSS, HTML) is almost <em>zero</em>.</p>
</li>
<li>
<p><strong>R has a huge community.</strong></p>
<p>Many R users just ask questions on websites like <a href="https://stackoverflow.com">StackOverflow.com</a>, the largest online community for programmers. At the time of writing, more than <a href="https://stackoverflow.com/questions/tagged/r?sort=votes">300,000 R-related questions</a> have already been asked on this platform (which covers questions and answers for any programming language). In my own experience, most questions are answered within a couple of minutes.</p>
</li>
<li>
<p><strong>R understands any data type, including SPSS/SAS/Stata.</strong></p>
<p>And that’s not vice versa I’m afraid. You can import data from any source into R. For example from SPSS, SAS and Stata (<a href="https://haven.tidyverse.org/">link</a>), from Minitab, Epi Info and EpiData (<a href="https://cran.r-project.org/package=foreign">link</a>), from Excel (<a href="https://readxl.tidyverse.org/">link</a>), from flat files like CSV, TXT or TSV (<a href="https://readr.tidyverse.org/">link</a>), or directly from databases and datawarehouses from anywhere on the world (<a href="https://dbplyr.tidyverse.org/">link</a>). You can even scrape websites to download tables that are live on the internet (<a href="https://github.com/hadley/rvest">link</a>) or get the results of an API call and transform it into data in only one command (<a href="https://github.com/Rdatatable/data.table/wiki/Convenience-features-of-fread">link</a>).</p>
<p>And the best part - you can export from R to most data formats as well. So you can import an SPSS file, do your analysis neatly in R and export the resulting tables to Excel files for sharing.</p>
</li>
<li>
<p><strong>R is completely free and open-source.</strong></p>
<p>No strings attached. It was created and is being maintained by volunteers who believe that (data) science should be open and publicly available to everybody. SPSS, SAS and Stata are quite expensive. IBM SPSS Staticstics only comes with subscriptions nowadays, varying <a href="https://www.ibm.com/products/spss-statistics/pricing">between USD 1,300 and USD 8,500</a> per user <em>per year</em>. SAS Analytics Pro costs <a href="https://www.sas.com/store/products-solutions/sas-analytics-pro/prodPERSANL.html">around USD 10,000</a> per computer. Stata also has a business model with subscription fees, varying <a href="https://www.stata.com/order/new/bus/single-user-licenses/dl/">between USD 600 and USD 2,800</a> per computer per year, but lower prices come with a limitation of the number of variables you can work with. And still they do not offer the above benefits of R.</p>
<p>If you are working at a midsized or small company, you can save it tens of thousands of dollars by using R instead of e.g. SPSS - gaining even more functions and flexibility. And all R enthousiasts can do as much PR as they want (like I do here), because nobody is officially associated with or affiliated by R. It is really free.</p>
</li>
<li>
<p><strong>R is (nowadays) the preferred analysis software in academic papers.</strong></p>
<p>At present, R is among the world most powerful statistical languages, and it is generally very popular in science (Bollmann <em>et al.</em>, 2017). For all the above reasons, the number of references to R as an analysis method in academic papers <a href="https://r4stats.com/2014/08/20/r-passes-spss-in-scholarly-use-stata-growing-rapidly/">is rising continuously</a> and has even surpassed SPSS for academic use (Muenchen, 2014).</p>
<p>I believe that the thing with SPSS is, that it has always had a great user interface which is very easy to learn and use. Back when they developed it, they had very little competition, let alone from R. R didn’t even had a professional user interface until the last decade (called RStudio, see below). How people used R between the nineties and 2010 is almost completely incomparable to how R is being used now. The language itself <a href="https://www.tidyverse.org/packages/">has been restyled completely</a> by volunteers who are dedicated professionals in the field of data science. SPSS was great when there was nothing else that could compete. But now in 2020, I don’t see any reason why SPSS would be of any better use than R.</p>
</li>
</ul>
<p>To demonstrate the first point:</p>
<div class="sourceCode" id="cb1"><html><body><pre class="r"><span class="co"># not all values are valid MIC values:</span>
<span class="fu"><a href="../reference/as.mic.html">as.mic</a></span>(<span class="fl">0.125</span>)
<span class="co"># Class &lt;mic&gt;</span>
<span class="co"># [1] 0.125</span>
<span class="fu"><a href="../reference/as.mic.html">as.mic</a></span>(<span class="st">"testvalue"</span>)
<span class="co"># Class &lt;mic&gt;</span>
<span class="co"># [1] &lt;NA&gt;</span>
<span class="co"># the Gram stain is avaiable for all bacteria:</span>
<span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>)
<span class="co"># [1] "Gram-negative"</span>
<span class="co"># Klebsiella is intrinsic resistant to amoxicllin, according to EUCAST:</span>
<span class="no">klebsiella_test</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span>(<span class="kw">mo</span> <span class="kw">=</span> <span class="st">"klebsiella"</span>,
<span class="kw">amox</span> <span class="kw">=</span> <span class="st">"S"</span>,
<span class="kw">stringsAsFactors</span> <span class="kw">=</span> <span class="fl">FALSE</span>)
<span class="no">klebsiella_test</span> <span class="co"># (our original data)</span>
<span class="co"># mo amox</span>
<span class="co"># 1 klebsiella S</span>
<span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span>(<span class="no">klebsiella_test</span>, <span class="kw">info</span> <span class="kw">=</span> <span class="fl">FALSE</span>) <span class="co"># (the edited data by EUCAST rules)</span>
<span class="co"># mo amox</span>
<span class="co"># 1 klebsiella R</span>
<span class="co"># hundreds of trade names can be translated to a name, trade name or an ATC code:</span>
<span class="fu"><a href="../reference/ab_property.html">ab_name</a></span>(<span class="st">"floxapen"</span>)
<span class="co"># [1] "Flucloxacillin"</span>
<span class="fu"><a href="../reference/ab_property.html">ab_tradenames</a></span>(<span class="st">"floxapen"</span>)
<span class="co"># [1] "floxacillin" "floxapen" "floxapen sodium salt"</span>
<span class="co"># [4] "fluclox" "flucloxacilina" "flucloxacillin" </span>
<span class="co"># [7] "flucloxacilline" "flucloxacillinum" "fluorochloroxacillin"</span>
<span class="fu"><a href="../reference/ab_property.html">ab_atc</a></span>(<span class="st">"floxapen"</span>)
<span class="co"># [1] "J01CF05"</span></pre></body></html></div>
</div>
<div id="import-data-from-spsssasstata" class="section level2">
<h2 class="hasAnchor">
<a href="#import-data-from-spsssasstata" class="anchor"></a>Import data from SPSS/SAS/Stata</h2>
<div id="rstudio" class="section level3">
<h3 class="hasAnchor">
<a href="#rstudio" class="anchor"></a>RStudio</h3>
<p>To work with R, probably the best option is to use <a href="https://www.rstudio.com/products/rstudio/">RStudio</a>. It is an open-source and free desktop environment which not only allows you to run R code, but also supports project management, version management, package management and convenient import menus to work with other data sources. You can also install <a href="https://www.rstudio.com/products/rstudio/">RStudio Server</a> on a private or corporate server, which brings nothing less than the complete RStudio software to you as a website (at home or at work).</p>
<p>To import a data file, just click <em>Import Dataset</em> in the Environment tab:</p>
<p><img src="https://github.com/msberends/AMR/raw/master/docs/import1.png"></p>
<p>If additional packages are needed, RStudio will ask you if they should be installed on beforehand.</p>
<p>In the the window that opens, you can define all options (parameters) that should be used for import and you’re ready to go:</p>
<p><img src="https://github.com/msberends/AMR/raw/master/docs/import2.png"></p>
<p>If you want named variables to be imported as factors so it resembles SPSS more, use <code><a href="https://haven.tidyverse.org/reference/as_factor.html">as_factor()</a></code>.</p>
<p>The difference is this:</p>
<div class="sourceCode" id="cb2"><html><body><pre class="r"><span class="no">SPSS_data</span>
<span class="co"># # A tibble: 4,203 x 4</span>
<span class="co"># v001 sex status statusage</span>
<span class="co"># &lt;dbl&gt; &lt;dbl+lbl&gt; &lt;dbl+lbl&gt; &lt;dbl&gt;</span>
<span class="co"># 1 10002 1 1 76.6</span>
<span class="co"># 2 10004 0 1 59.1</span>
<span class="co"># 3 10005 1 1 54.5</span>
<span class="co"># 4 10006 1 1 54.1</span>
<span class="co"># 5 10007 1 1 57.7</span>
<span class="co"># 6 10008 1 1 62.8</span>
<span class="co"># 7 10010 0 1 63.7</span>
<span class="co"># 8 10011 1 1 73.1</span>
<span class="co"># 9 10017 1 1 56.7</span>
<span class="co"># 10 10018 0 1 66.6</span>
<span class="co"># # … with 4,193 more rows</span>
<span class="fu">as_factor</span>(<span class="no">SPSS_data</span>)
<span class="co"># # A tibble: 4,203 x 4</span>
<span class="co"># v001 sex status statusage</span>
<span class="co"># &lt;dbl&gt; &lt;fct&gt; &lt;fct&gt; &lt;dbl&gt;</span>
<span class="co"># 1 10002 Male alive 76.6</span>
<span class="co"># 2 10004 Female alive 59.1</span>
<span class="co"># 3 10005 Male alive 54.5</span>
<span class="co"># 4 10006 Male alive 54.1</span>
<span class="co"># 5 10007 Male alive 57.7</span>
<span class="co"># 6 10008 Male alive 62.8</span>
<span class="co"># 7 10010 Female alive 63.7</span>
<span class="co"># 8 10011 Male alive 73.1</span>
<span class="co"># 9 10017 Male alive 56.7</span>
<span class="co"># 10 10018 Female alive 66.6</span>
<span class="co"># # … with 4,193 more rows</span></pre></body></html></div>
</div>
<div id="base-r" class="section level3">
<h3 class="hasAnchor">
<a href="#base-r" class="anchor"></a>Base R</h3>
<p>To import data from SPSS, SAS or Stata, you can use the <a href="https://haven.tidyverse.org/">great <code>haven</code> package</a> yourself:</p>
<div class="sourceCode" id="cb3"><html><body><pre class="r"><span class="co"># download and install the latest version:</span>
<span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html">install.packages</a></span>(<span class="st">"haven"</span>)
<span class="co"># load the package you just installed:</span>
<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="no">haven</span>)</pre></body></html></div>
<p>You can now import files as follows:</p>
<div id="spss" class="section level4">
<h4 class="hasAnchor">
<a href="#spss" class="anchor"></a>SPSS</h4>
<p>To read files from SPSS into R:</p>
<div class="sourceCode" id="cb4"><html><body><pre class="r"><span class="co"># read any SPSS file based on file extension (best way):</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">read_spss</a></span>(<span class="kw">file</span> <span class="kw">=</span> <span class="st">"path/to/file"</span>)
<span class="co"># read .sav or .zsav file:</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">read_sav</a></span>(<span class="kw">file</span> <span class="kw">=</span> <span class="st">"path/to/file"</span>)
<span class="co"># read .por file:</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">read_por</a></span>(<span class="kw">file</span> <span class="kw">=</span> <span class="st">"path/to/file"</span>)</pre></body></html></div>
<p>Do not forget about <code><a href="https://haven.tidyverse.org/reference/as_factor.html">as_factor()</a></code>, as mentioned above.</p>
<p>To export your R objects to the SPSS file format:</p>
<div class="sourceCode" id="cb5"><html><body><pre class="r"><span class="co"># save as .sav file:</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">write_sav</a></span>(<span class="kw">data</span> <span class="kw">=</span> <span class="no">yourdata</span>, <span class="kw">path</span> <span class="kw">=</span> <span class="st">"path/to/file"</span>)
<span class="co"># save as compressed .zsav file:</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_spss.html">write_sav</a></span>(<span class="kw">data</span> <span class="kw">=</span> <span class="no">yourdata</span>, <span class="kw">path</span> <span class="kw">=</span> <span class="st">"path/to/file"</span>, <span class="kw">compress</span> <span class="kw">=</span> <span class="fl">TRUE</span>)</pre></body></html></div>
</div>
<div id="sas" class="section level4">
<h4 class="hasAnchor">
<a href="#sas" class="anchor"></a>SAS</h4>
<p>To read files from SAS into R:</p>
<div class="sourceCode" id="cb6"><html><body><pre class="r"><span class="co"># read .sas7bdat + .sas7bcat files:</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_sas.html">read_sas</a></span>(<span class="kw">data_file</span> <span class="kw">=</span> <span class="st">"path/to/file"</span>, <span class="kw">catalog_file</span> <span class="kw">=</span> <span class="kw">NULL</span>)
<span class="co"># read SAS transport files (version 5 and version 8):</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_xpt.html">read_xpt</a></span>(<span class="kw">file</span> <span class="kw">=</span> <span class="st">"path/to/file"</span>)</pre></body></html></div>
<p>To export your R objects to the SAS file format:</p>
<div class="sourceCode" id="cb7"><html><body><pre class="r"><span class="co"># save as regular SAS file:</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_sas.html">write_sas</a></span>(<span class="kw">data</span> <span class="kw">=</span> <span class="no">yourdata</span>, <span class="kw">path</span> <span class="kw">=</span> <span class="st">"path/to/file"</span>)
<span class="co"># the SAS transport format is an open format </span>
<span class="co"># (required for submission of the data to the FDA)</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_xpt.html">write_xpt</a></span>(<span class="kw">data</span> <span class="kw">=</span> <span class="no">yourdata</span>, <span class="kw">path</span> <span class="kw">=</span> <span class="st">"path/to/file"</span>, <span class="kw">version</span> <span class="kw">=</span> <span class="fl">8</span>)</pre></body></html></div>
</div>
<div id="stata" class="section level4">
<h4 class="hasAnchor">
<a href="#stata" class="anchor"></a>Stata</h4>
<p>To read files from Stata into R:</p>
<div class="sourceCode" id="cb8"><html><body><pre class="r"><span class="co"># read .dta file:</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html">read_stata</a></span>(<span class="kw">file</span> <span class="kw">=</span> <span class="st">"/path/to/file"</span>)
<span class="co"># works exactly the same:</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html">read_dta</a></span>(<span class="kw">file</span> <span class="kw">=</span> <span class="st">"/path/to/file"</span>)</pre></body></html></div>
<p>To export your R objects to the Stata file format:</p>
<div class="sourceCode" id="cb9"><html><body><pre class="r"><span class="co"># save as .dta file, Stata version 14:</span>
<span class="co"># (supports Stata v8 until v15 at the time of writing)</span>
<span class="fu"><a href="https://haven.tidyverse.org/reference/read_dta.html">write_dta</a></span>(<span class="kw">data</span> <span class="kw">=</span> <span class="no">yourdata</span>, <span class="kw">path</span> <span class="kw">=</span> <span class="st">"/path/to/file"</span>, <span class="kw">version</span> <span class="kw">=</span> <span class="fl">14</span>)</pre></body></html></div>
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