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(v1.7.1.9030) unit test

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dr. M.S. (Matthijs) Berends
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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">1.7.1.9025</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9030</span>
</span>
</div>
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<div class="page-header"><h1 class="hasAnchor">
<a href="#amr-for-r-" class="anchor" aria-hidden="true"></a><code>AMR</code> (for R) <img src="./logo.png" align="right" height="120px">
</h1></div>
<blockquote>
<p>This package formed the basis of two PhD theses, of which the first was published and defended on 25 August 2021. Click here to read it: <a href="https://doi.org/10.33612/diss.177417131" class="external-link">DOI 10.33612/diss.177417131</a>.</p>
</blockquote>
<div id="what-is-amr-for-r" class="section level3">
<h3 class="hasAnchor">
<a href="#what-is-amr-for-r" class="anchor" aria-hidden="true"></a>What is <code>AMR</code> (for R)?</h3>
<p><em>(To find out how to conduct AMR data analysis, please <a href="./articles/AMR.html">continue reading here to get started</a>.)</em></p>
<p><code>AMR</code> is a free, open-source and independent <a href="https://www.r-project.org" class="external-link">R package</a> to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. <strong>Our aim is to provide a standard</strong> for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.</p>
<p>After installing this package, R knows <a href="./reference/microorganisms.html"><strong>~70,000 distinct microbial species</strong></a> and all <a href="./reference/antibiotics.html"><strong>~550 antibiotic, antimycotic and antiviral drugs</strong></a> by name and code (including ATC, EARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.</p>
<p>This package is <a href="https://en.wikipedia.org/wiki/Dependency_hell" class="external-link">fully independent of any other R package</a> and works on Windows, macOS and Linux with all versions of R since R-3.0.0 (April 2013). <strong>It was designed to work in any setting, including those with very limited resources</strong>. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the <a href="https://www.rug.nl" class="external-link">University of Groningen</a>, in collaboration with non-profit organisations <a href="https://www.certe.nl" class="external-link">Certe Medical Diagnostics and Advice Foundation</a> and <a href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a>. This R package is <a href="./news">actively maintained</a> and is free software (see <a href="#copyright">Copyright</a>).</p>