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<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Predict Antimicrobial Resistance — resistance_predict • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Predict Antimicrobial Resistance — resistance_predict"><meta name="description" content="Create a prediction model to predict antimicrobial resistance for the next years. Standard errors (SE) will be returned as columns se_min and se_max. See Examples for a real live example.
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NOTE: These functions are deprecated and will be removed in a future version. Use the AMR package combined with the tidymodels framework instead, for which we have written a basic and short introduction on our website."><meta property="og:description" content="Create a prediction model to predict antimicrobial resistance for the next years. Standard errors (SE) will be returned as columns se_min and se_max. See Examples for a real live example.
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NOTE: These functions are deprecated and will be removed in a future version. Use the AMR package combined with the tidymodels framework instead, for which we have written a basic and short introduction on our website."><meta property="og:image" content="https://amr-for-r.org/logo.svg"><link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/katex@0.16.11/dist/katex.min.css" integrity="sha384-nB0miv6/jRmo5UMMR1wu3Gz6NLsoTkbqJghGIsx//Rlm+ZU03BU6SQNC66uf4l5+" crossorigin="anonymous"><script defer src="https://cdn.jsdelivr.net/npm/katex@0.16.11/dist/katex.min.js" integrity="sha384-7zkQWkzuo3B5mTepMUcHkMB5jZaolc2xDwL6VFqjFALcbeS9Ggm/Yr2r3Dy4lfFg" crossorigin="anonymous"></script><script defer src="https://cdn.jsdelivr.net/npm/katex@0.16.11/dist/contrib/auto-render.min.js" integrity="sha384-43gviWU0YVjaDtb/GhzOouOXtZMP/7XUzwPTstBeZFe/+rCMvRwr4yROQP43s0Xk" crossorigin="anonymous" onload="renderMathInElement(document.body);"></script></head><body>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9239</small>
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<ul class="dropdown-menu" aria-labelledby="dropdown-how-to"><li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
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<li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
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<img src="../logo.svg" class="logo" alt=""><h1>Predict Antimicrobial Resistance</h1>
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<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/resistance_predict.R" class="external-link"><code>R/resistance_predict.R</code></a></small>
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<div class="d-none name"><code>resistance_predict.Rd</code></div>
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</div>
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<div class="ref-description section level2">
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<p>Create a prediction model to predict antimicrobial resistance for the next years. Standard errors (SE) will be returned as columns <code>se_min</code> and <code>se_max</code>. See <em>Examples</em> for a real live example.</p>
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<p><strong>NOTE:</strong> These functions are <a href="AMR-deprecated.html">deprecated</a> and will be removed in a future version. Use the AMR package combined with the tidymodels framework instead, for which we have written a <a href="https://amr-for-r.org/articles/AMR_with_tidymodels.html">basic and short introduction on our website</a>.</p>
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</div>
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<div class="section level2">
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<h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
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<div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">resistance_predict</span><span class="op">(</span><span class="va">x</span>, <span class="va">col_ab</span>, col_date <span class="op">=</span> <span class="cn">NULL</span>, year_min <span class="op">=</span> <span class="cn">NULL</span>,</span>
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<span> year_max <span class="op">=</span> <span class="cn">NULL</span>, year_every <span class="op">=</span> <span class="fl">1</span>, minimum <span class="op">=</span> <span class="fl">30</span>, model <span class="op">=</span> <span class="cn">NULL</span>,</span>
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<span> I_as_S <span class="op">=</span> <span class="cn">TRUE</span>, preserve_measurements <span class="op">=</span> <span class="cn">TRUE</span>, info <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/interactive.html" class="external-link">interactive</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
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<span></span>
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<span><span class="fu">sir_predict</span><span class="op">(</span><span class="va">x</span>, <span class="va">col_ab</span>, col_date <span class="op">=</span> <span class="cn">NULL</span>, year_min <span class="op">=</span> <span class="cn">NULL</span>, year_max <span class="op">=</span> <span class="cn">NULL</span>,</span>
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<span> year_every <span class="op">=</span> <span class="fl">1</span>, minimum <span class="op">=</span> <span class="fl">30</span>, model <span class="op">=</span> <span class="cn">NULL</span>, I_as_S <span class="op">=</span> <span class="cn">TRUE</span>,</span>
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<span> preserve_measurements <span class="op">=</span> <span class="cn">TRUE</span>, info <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/interactive.html" class="external-link">interactive</a></span><span class="op">(</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
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<span></span>
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<span><span class="co"># S3 method for class 'resistance_predict'</span></span>
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<span><span class="fu"><a href="plot.html">plot</a></span><span class="op">(</span><span class="va">x</span>, main <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Resistance Prediction of"</span>,</span>
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<span> <span class="va">x_name</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
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<span></span>
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<span><span class="fu">ggplot_sir_predict</span><span class="op">(</span><span class="va">x</span>, main <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Resistance Prediction of"</span>, <span class="va">x_name</span><span class="op">)</span>,</span>
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<span> ribbon <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span></span>
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<span></span>
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<span><span class="co"># S3 method for class 'resistance_predict'</span></span>
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<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span><span class="va">object</span>,</span>
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<span> main <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Resistance Prediction of"</span>, <span class="va">x_name</span><span class="op">)</span>, ribbon <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
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</div>
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<div class="section level2">
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<h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
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<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
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<dd><p>A <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> containing isolates. Can be left blank for automatic determination, see <em>Examples</em>.</p></dd>
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<dt id="arg-col-ab">col_ab<a class="anchor" aria-label="anchor" href="#arg-col-ab"></a></dt>
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<dd><p>Column name of <code>x</code> containing antimicrobial interpretations (<code>"R"</code>, <code>"I"</code> and <code>"S"</code>).</p></dd>
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<dt id="arg-col-date">col_date<a class="anchor" aria-label="anchor" href="#arg-col-date"></a></dt>
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<dd><p>Column name of the date, will be used to calculate years if this column doesn't consist of years already - the default is the first column of with a date class.</p></dd>
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<dt id="arg-year-min">year_min<a class="anchor" aria-label="anchor" href="#arg-year-min"></a></dt>
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<dd><p>Lowest year to use in the prediction model, dafaults to the lowest year in <code>col_date</code>.</p></dd>
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<dt id="arg-year-max">year_max<a class="anchor" aria-label="anchor" href="#arg-year-max"></a></dt>
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<dd><p>Highest year to use in the prediction model - the default is 10 years after today.</p></dd>
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<dt id="arg-year-every">year_every<a class="anchor" aria-label="anchor" href="#arg-year-every"></a></dt>
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<dd><p>Unit of sequence between lowest year found in the data and <code>year_max</code>.</p></dd>
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<dt id="arg-minimum">minimum<a class="anchor" aria-label="anchor" href="#arg-minimum"></a></dt>
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<dd><p>Minimal amount of available isolates per year to include. Years containing less observations will be estimated by the model.</p></dd>
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<dt id="arg-model">model<a class="anchor" aria-label="anchor" href="#arg-model"></a></dt>
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<dd><p>The statistical model of choice. This could be a generalised linear regression model with binomial distribution (i.e. using <code>glm(..., family = binomial)</code>, assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance. See <em>Details</em> for all valid options.</p></dd>
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<dt id="arg-i-as-s">I_as_S<a class="anchor" aria-label="anchor" href="#arg-i-as-s"></a></dt>
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<dd><p>A <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether values <code>"I"</code> should be treated as <code>"S"</code> (will otherwise be treated as <code>"R"</code>). The default, <code>TRUE</code>, follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section <em>Interpretation of S, I and R</em> below.</p></dd>
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<dt id="arg-preserve-measurements">preserve_measurements<a class="anchor" aria-label="anchor" href="#arg-preserve-measurements"></a></dt>
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<dd><p>A <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether predictions of years that are actually available in the data should be overwritten by the original data. The standard errors of those years will be <code>NA</code>.</p></dd>
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<dt id="arg-info">info<a class="anchor" aria-label="anchor" href="#arg-info"></a></dt>
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<dd><p>A <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether textual analysis should be printed with the name and <code><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary()</a></code> of the statistical model.</p></dd>
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<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
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<dd><p>Arguments passed on to functions.</p></dd>
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<dt id="arg-main">main<a class="anchor" aria-label="anchor" href="#arg-main"></a></dt>
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<dd><p>Title of the plot.</p></dd>
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<dt id="arg-ribbon">ribbon<a class="anchor" aria-label="anchor" href="#arg-ribbon"></a></dt>
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<dd><p>A <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether a ribbon should be shown (default) or error bars.</p></dd>
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<dt id="arg-object">object<a class="anchor" aria-label="anchor" href="#arg-object"></a></dt>
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<dd><p>Model data to be plotted.</p></dd>
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</dl></div>
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<div class="section level2">
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<h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
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<p>A <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with extra class <code>resistance_predict</code> with columns:</p><ul><li><p><code>year</code></p></li>
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<li><p><code>value</code>, the same as <code>estimated</code> when <code>preserve_measurements = FALSE</code>, and a combination of <code>observed</code> and <code>estimated</code> otherwise</p></li>
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<li><p><code>se_min</code>, the lower bound of the standard error with a minimum of <code>0</code> (so the standard error will never go below 0%)</p></li>
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<li><p><code>se_max</code> the upper bound of the standard error with a maximum of <code>1</code> (so the standard error will never go above 100%)</p></li>
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<li><p><code>observations</code>, the total number of available observations in that year, i.e. \(S + I + R\)</p></li>
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<li><p><code>observed</code>, the original observed resistant percentages</p></li>
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<li><p><code>estimated</code>, the estimated resistant percentages, calculated by the model</p></li>
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</ul><p>Furthermore, the model itself is available as an attribute: <code>attributes(x)$model</code>, see <em>Examples</em>.</p>
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</div>
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<div class="section level2">
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<h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
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<p>Valid options for the statistical model (argument <code>model</code>) are:</p><ul><li><p><code>"binomial"</code> or <code>"binom"</code> or <code>"logit"</code>: a generalised linear regression model with binomial distribution</p></li>
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<li><p><code>"loglin"</code> or <code>"poisson"</code>: a generalised log-linear regression model with poisson distribution</p></li>
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<li><p><code>"lin"</code> or <code>"linear"</code>: a linear regression model</p></li>
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</ul></div>
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<div class="section level2">
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<h2 id="interpretation-of-sir">Interpretation of SIR<a class="anchor" aria-label="anchor" href="#interpretation-of-sir"></a></h2>
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<p>In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories S, I, and R (<a href="https://www.eucast.org/newsiandr" class="external-link">https://www.eucast.org/newsiandr</a>).</p>
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<p>This AMR package follows insight; use <code><a href="proportion.html">susceptibility()</a></code> (equal to <code><a href="proportion.html">proportion_SI()</a></code>) to determine antimicrobial susceptibility and <code><a href="count.html">count_susceptible()</a></code> (equal to <code><a href="count.html">count_SI()</a></code>) to count susceptible isolates.</p>
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</div>
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<div class="section level2">
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<h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
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<div class="dont-index"><p>The <code><a href="proportion.html">proportion()</a></code> functions to calculate resistance</p>
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<p>Models: <code><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm()</a></code> <code><a href="https://rdrr.io/r/stats/glm.html" class="external-link">glm()</a></code></p></div>
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</div>
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<div class="section level2">
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<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
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<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">x</span> <span class="op"><-</span> <span class="fu">resistance_predict</span><span class="op">(</span><span class="va">example_isolates</span>,</span></span>
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<span class="r-in"><span> col_ab <span class="op">=</span> <span class="st">"AMX"</span>,</span></span>
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<span class="r-in"><span> year_min <span class="op">=</span> <span class="fl">2010</span>,</span></span>
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<span class="r-in"><span> model <span class="op">=</span> <span class="st">"binomial"</span></span></span>
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<span class="r-in"><span><span class="op">)</span></span></span>
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<span class="r-wrn co"><span class="r-pr">#></span> <span class="warning">Warning: </span>The <span style="background-color: #EEEEEE;">resistance_predict()</span> function is deprecated and will be removed in a</span>
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<span class="r-wrn co"><span class="r-pr">#></span> future version, see <span style="background-color: #EEEEEE;">?AMR-deprecated</span>. Use the tidymodels framework</span>
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<span class="r-wrn co"><span class="r-pr">#></span> instead, for which we have written a basic and short introduction on our</span>
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<span class="r-wrn co"><span class="r-pr">#></span> website: https://amr-for-r.org/articles/AMR_with_tidymodels.html</span>
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<span class="r-wrn co"><span class="r-pr">#></span> This warning will be shown once per session.</span>
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<span class="r-in"><span><span class="fu"><a href="plot.html">plot</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></span>
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<span class="r-plt img"><img src="resistance_predict-1.png" alt="" width="700" height="433"></span>
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<span class="r-in"><span><span class="co"># \donttest{</span></span></span>
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<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://ggplot2.tidyverse.org" class="external-link">"ggplot2"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
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<span class="r-in"><span> <span class="fu">ggplot_sir_predict</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></span>
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<span class="r-in"><span><span class="op">}</span></span></span>
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<span class="r-plt img"><img src="resistance_predict-2.png" alt="" width="700" height="433"></span>
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<span class="r-in"><span></span></span>
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<span class="r-in"><span><span class="co"># using dplyr:</span></span></span>
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<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
|
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<span class="r-in"><span> <span class="va">x</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
|
<span class="r-in"><span> <span class="fu"><a href="first_isolate.html">filter_first_isolate</a></span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
|
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Staphylococcus"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
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<span class="r-in"><span> <span class="fu">resistance_predict</span><span class="op">(</span><span class="st">"PEN"</span>, model <span class="op">=</span> <span class="st">"binomial"</span><span class="op">)</span></span></span>
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<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="fu"><a href="plot.html">plot</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span><span class="op">)</span></span></span>
|
|
<span class="r-in"><span></span></span>
|
|
<span class="r-in"><span> <span class="co"># get the model from the object</span></span></span>
|
|
<span class="r-in"><span> <span class="va">mymodel</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/attributes.html" class="external-link">attributes</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span><span class="op">$</span><span class="va">model</span></span></span>
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|
<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">mymodel</span><span class="op">)</span></span></span>
|
|
<span class="r-in"><span><span class="op">}</span></span></span>
|
|
<span class="r-plt img"><img src="resistance_predict-3.png" alt="" width="700" height="433"></span>
|
|
<span class="r-out co"><span class="r-pr">#></span> NULL</span>
|
|
<span class="r-out co"><span class="r-pr">#></span> </span>
|
|
<span class="r-out co"><span class="r-pr">#></span> Call:</span>
|
|
<span class="r-out co"><span class="r-pr">#></span> glm(formula = df_matrix ~ year, family = binomial)</span>
|
|
<span class="r-out co"><span class="r-pr">#></span> </span>
|
|
<span class="r-out co"><span class="r-pr">#></span> Coefficients:</span>
|
|
<span class="r-out co"><span class="r-pr">#></span> Estimate Std. Error z value Pr(>|z|)</span>
|
|
<span class="r-out co"><span class="r-pr">#></span> (Intercept) 35.76101 72.29172 0.495 0.621</span>
|
|
<span class="r-out co"><span class="r-pr">#></span> year -0.01720 0.03603 -0.477 0.633</span>
|
|
<span class="r-out co"><span class="r-pr">#></span> </span>
|
|
<span class="r-out co"><span class="r-pr">#></span> (Dispersion parameter for binomial family taken to be 1)</span>
|
|
<span class="r-out co"><span class="r-pr">#></span> </span>
|
|
<span class="r-out co"><span class="r-pr">#></span> Null deviance: 5.3681 on 11 degrees of freedom</span>
|
|
<span class="r-out co"><span class="r-pr">#></span> Residual deviance: 5.1408 on 10 degrees of freedom</span>
|
|
<span class="r-out co"><span class="r-pr">#></span> AIC: 50.271</span>
|
|
<span class="r-out co"><span class="r-pr">#></span> </span>
|
|
<span class="r-out co"><span class="r-pr">#></span> Number of Fisher Scoring iterations: 4</span>
|
|
<span class="r-out co"><span class="r-pr">#></span> </span>
|
|
<span class="r-in"><span></span></span>
|
|
<span class="r-in"><span><span class="co"># create nice plots with ggplot2 yourself</span></span></span>
|
|
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span> <span class="op">&&</span> <span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://ggplot2.tidyverse.org" class="external-link">"ggplot2"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
|
|
<span class="r-in"><span> <span class="va">data</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
|
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">mo</span> <span class="op">==</span> <span class="fu"><a href="as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
|
<span class="r-in"><span> <span class="fu">resistance_predict</span><span class="op">(</span></span></span>
|
|
<span class="r-in"><span> col_ab <span class="op">=</span> <span class="st">"AMX"</span>,</span></span>
|
|
<span class="r-in"><span> col_date <span class="op">=</span> <span class="st">"date"</span>,</span></span>
|
|
<span class="r-in"><span> model <span class="op">=</span> <span class="st">"binomial"</span>,</span></span>
|
|
<span class="r-in"><span> info <span class="op">=</span> <span class="cn">FALSE</span>,</span></span>
|
|
<span class="r-in"><span> minimum <span class="op">=</span> <span class="fl">15</span></span></span>
|
|
<span class="r-in"><span> <span class="op">)</span></span></span>
|
|
<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></span>
|
|
<span class="r-in"><span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></span>
|
|
<span class="r-in"><span><span class="op">}</span></span></span>
|
|
<span class="r-plt img"><img src="resistance_predict-4.png" alt="" width="700" height="433"></span>
|
|
<span class="r-in"><span><span class="co"># }</span></span></span>
|
|
</code></pre></div>
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</div>
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</main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
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</nav></aside></div>
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<footer><div class="pkgdown-footer-left">
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<p><code>AMR</code> (for R). Free and open-source, licenced under the <a target="_blank" href="https://github.com/msberends/AMR/blob/main/LICENSE" class="external-link">GNU General Public License version 2.0 (GPL-2)</a>.<br>Developed at the <a target="_blank" href="https://www.rug.nl" class="external-link">University of Groningen</a> and <a target="_blank" href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a> in The Netherlands.</p>
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</div>
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<div class="pkgdown-footer-right">
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<p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://amr-for-r.org/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://amr-for-r.org/logo_umcg.svg" style="max-width: 150px;"></a></p>
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