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<h1>Predict antimicrobial resistance</h1>
<div class="hidden name"><code>resistance_predict.Rd</code></div>
</div>
<div class="ref-description">
<p>Create a prediction model to predict antimicrobial resistance for the next years on statistical solid ground. Standard errors (SE) will be returned as columns <code>se_min</code> and <code>se_max</code>. See Examples for a real live example.</p>
</div>
<pre class="usage"><span class='fu'>resistance_predict</span>(<span class='no'>x</span>, <span class='no'>col_ab</span>, <span class='kw'>col_date</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>year_min</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
<span class='kw'>year_max</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>year_every</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>,
<span class='kw'>model</span> <span class='kw'>=</span> <span class='st'>"binomial"</span>, <span class='kw'>I_as_S</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>preserve_measurements</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>info</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='no'>...</span>)
<span class='fu'>rsi_predict</span>(<span class='no'>x</span>, <span class='no'>col_ab</span>, <span class='kw'>col_date</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>year_min</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
<span class='kw'>year_max</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>year_every</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>,
<span class='kw'>model</span> <span class='kw'>=</span> <span class='st'>"binomial"</span>, <span class='kw'>I_as_S</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>preserve_measurements</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>info</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='no'>...</span>)
<span class='co'># S3 method for resistance_predict</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/graphics/topics/plot'>plot</a></span>(<span class='no'>x</span>,
<span class='kw'>main</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/paste'>paste</a></span>(<span class='st'>"Resistance Prediction of"</span>, <span class='no'>x_name</span>), <span class='no'>...</span>)
<span class='fu'>ggplot_rsi_predict</span>(<span class='no'>x</span>, <span class='kw'>main</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/paste'>paste</a></span>(<span class='st'>"Resistance Prediction of"</span>, <span class='no'>x_name</span>),
<span class='kw'>ribbon</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='no'>...</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>x</th>
<td><p>a <code>data.frame</code> containing isolates.</p></td>
</tr>
<tr>
<th>col_ab</th>
<td><p>column name of <code>x</code> with antimicrobial interpretations (<code>R</code>, <code>I</code> and <code>S</code>)</p></td>
</tr>
<tr>
<th>col_date</th>
<td><p>column name of the date, will be used to calculate years if this column doesn't consist of years already, defaults to the first column of with a date class</p></td>
</tr>
<tr>
<th>year_min</th>
<td><p>lowest year to use in the prediction model, dafaults to the lowest year in <code>col_date</code></p></td>
</tr>
<tr>
<th>year_max</th>
<td><p>highest year to use in the prediction model, defaults to 10 years after today</p></td>
</tr>
<tr>
<th>year_every</th>
<td><p>unit of sequence between lowest year found in the data and <code>year_max</code></p></td>
</tr>
<tr>
<th>minimum</th>
<td><p>minimal amount of available isolates per year to include. Years containing less observations will be estimated by the model.</p></td>
</tr>
<tr>
<th>model</th>
<td><p>the statistical model of choice. Defaults to a generalised linear regression model with binomial distribution, assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance. See Details for valid options.</p></td>
</tr>
<tr>
<th>I_as_S</th>
<td><p>a logical to indicate whether values <code>I</code> should be treated as <code>S</code></p></td>
</tr>
<tr>
<th>preserve_measurements</th>
<td><p>a logical 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></td>
</tr>
<tr>
<th>info</th>
<td><p>a logical to indicate whether textual analysis should be printed with the name and <code><a href='https://www.rdocumentation.org/packages/base/topics/summary'>summary</a></code> of the statistical model.</p></td>
</tr>
<tr>
<th>...</th>
<td><p>parameters passed on to functions</p></td>
</tr>
<tr>
<th>main</th>
<td><p>title of the plot</p></td>
</tr>
<tr>
<th>ribbon</th>
<td><p>a logical to indicate whether a ribbon should be shown (default) or error bars</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p><code>data.frame</code> with extra class <code>"resistance_predict"</code> with columns:</p><ul>
<li><p><code>year</code></p></li>
<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>
<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>
<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>
<li><p><code>observations</code>, the total number of available observations in that year, i.e. S + I + R</p></li>
<li><p><code>observed</code>, the original observed resistant percentages</p></li>
<li><p><code>estimated</code>, the estimated resistant percentages, calculated by the model</p></li>
</ul><p>Furthermore, the model itself is available as an attribute: <code>attributes(x)$model</code>, see Examples.</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>Valid options for the statistical model 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>
<li><p><code>"loglin"</code> or <code>"poisson"</code>: a generalised log-linear regression model with poisson distribution</p></li>
<li><p><code>"lin"</code> or <code>"linear"</code>: a linear regression model</p></li>
</ul>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p>The <code><a href='portion.html'>portion</a></code> function to calculate resistance, <br /> <code><a href='https://www.rdocumentation.org/packages/stats/topics/lm'>lm</a></code> <code><a href='https://www.rdocumentation.org/packages/stats/topics/glm'>glm</a></code></p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='no'>x</span> <span class='kw'>&lt;-</span> <span class='fu'>resistance_predict</span>(<span class='no'>septic_patients</span>, <span class='kw'>col_ab</span> <span class='kw'>=</span> <span class='st'>"AMX"</span>, <span class='kw'>year_min</span> <span class='kw'>=</span> <span class='fl'>2010</span>)
<span class='fu'><a href='https://www.rdocumentation.org/packages/graphics/topics/plot'>plot</a></span>(<span class='no'>x</span>)
<span class='fu'>ggplot_rsi_predict</span>(<span class='no'>x</span>)
<span class='co'># use dplyr so you can actually read it:</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='no'>x</span> <span class='kw'>&lt;-</span> <span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='first_isolate.html'>filter_first_isolate</a></span>() <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='fu'><a href='mo_property.html'>mo_genus</a></span>(<span class='no'>mo</span>) <span class='kw'>==</span> <span class='st'>"Staphylococcus"</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>resistance_predict</span>(<span class='st'>"PEN"</span>)
<span class='fu'><a href='https://www.rdocumentation.org/packages/graphics/topics/plot'>plot</a></span>(<span class='no'>x</span>)
<span class='co'># get the model from the object</span>
<span class='no'>mymodel</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/attributes'>attributes</a></span>(<span class='no'>x</span>)$<span class='no'>model</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/summary'>summary</a></span>(<span class='no'>mymodel</span>)
<span class='co'># create nice plots with ggplot2 yourself</span>
<span class='kw'>if</span> (!<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>require</a></span>(<span class='no'>ggplot2</span>)) {
<span class='no'>data</span> <span class='kw'>&lt;-</span> <span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>mo</span> <span class='kw'>==</span> <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='st'>"E. coli"</span>)) <span class='kw'>%&gt;%</span>
<span class='fu'>resistance_predict</span>(<span class='kw'>col_ab</span> <span class='kw'>=</span> <span class='st'>"AMX"</span>,
<span class='kw'>col_date</span> <span class='kw'>=</span> <span class='st'>"date"</span>,
<span class='kw'>info</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
<span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>15</span>)
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggplot.html'>ggplot</a></span>(<span class='no'>data</span>,
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/aes.html'>aes</a></span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='no'>year</span>)) +
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/geom_bar.html'>geom_col</a></span>(<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/aes.html'>aes</a></span>(<span class='kw'>y</span> <span class='kw'>=</span> <span class='no'>value</span>),
<span class='kw'>fill</span> <span class='kw'>=</span> <span class='st'>"grey75"</span>) +
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/geom_linerange.html'>geom_errorbar</a></span>(<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/aes.html'>aes</a></span>(<span class='kw'>ymin</span> <span class='kw'>=</span> <span class='no'>se_min</span>,
<span class='kw'>ymax</span> <span class='kw'>=</span> <span class='no'>se_max</span>),
<span class='kw'>colour</span> <span class='kw'>=</span> <span class='st'>"grey50"</span>) +
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/scale_continuous.html'>scale_y_continuous</a></span>(<span class='kw'>limits</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='fl'>0</span>, <span class='fl'>1</span>),
<span class='kw'>breaks</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/seq'>seq</a></span>(<span class='fl'>0</span>, <span class='fl'>1</span>, <span class='fl'>0.1</span>),
<span class='kw'>labels</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/paste'>paste0</a></span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/seq'>seq</a></span>(<span class='fl'>0</span>, <span class='fl'>100</span>, <span class='fl'>10</span>), <span class='st'>"%"</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='fu'><a href='https://www.rdocumentation.org/packages/base/topics/expression'>expression</a></span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/paste'>paste</a></span>(<span class='st'>"Forecast of amoxicillin resistance in "</span>,
<span class='fu'><a href='https://www.rdocumentation.org/packages/grDevices/topics/plotmath'>italic</a></span>(<span class='st'>"E. coli"</span>))),
<span class='kw'>y</span> <span class='kw'>=</span> <span class='st'>"%IR"</span>,
<span class='kw'>x</span> <span class='kw'>=</span> <span class='st'>"Year"</span>) +
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggtheme.html'>theme_minimal</a></span>(<span class='kw'>base_size</span> <span class='kw'>=</span> <span class='fl'>13</span>)
}
<span class='co'># }</span></pre>
</div>
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<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#arguments">Arguments</a></li>
<li><a href="#value">Value</a></li>
<li><a href="#details">Details</a></li>
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