doROCavg

Empirically average over multiple empirical ROC curves

This software does Multi-Reader, Multi-Case (MRMC) analyses of data from imaging studies where clinicians (readers) evaluate patient images (cases). What does this mean? ... Many imaging studies are designed so that every reader reads every case in all modalities, a fully-crossed study. In this case, the data is cross-correlated, and we consider the readers and cases to be cross-correlated random effects. An MRMC analysis accounts for the variability and correlations from the readers and cases when estimating variances, confidence intervals, and p-values. The functions in this package can treat arbitrary study designs and studies with missing data, not just fully-crossed study designs. An overview of this software, including references presenting details on the methods, can be found here: <https://www.fda.gov/medical-devices/science-and-research-medical-devices/imrmc-software-do-multi-reader-multi-case-statistical-analysis-reader-studies>.

Brandon Gallas

iMRMC

Multi-Reader, Multi-Case Analysis Methods (ROC, Agreement, and
Other Metrics)

doROCavg function

<dl><dt>ROC</dt>
<dd>list of ROC curves. Each element of the list
is a data frame with pairs of (fpf, tpf) operating points.</dd>
<dt>direction</dt>
<dd>the direction over which to average<ul>
<li><code>SeSp</code> (default) The ROC curves are averaged diagonally.
 Average Se+Sp of all the input ROC curves
 for every possible Se-Sp.</li>
<li><code>Se</code> The ROC curves are averaged vertically.
 Average the sensitivity of all the input ROC curves
 for every possible specificity.</li>
<li><code>Sp</code> The ROC curves are averaged horizontally.
 Average the specificity of all the input ROC curves
 for every possible specificity.</li>
</ul></dd></dl>

Arguments

Empirically average over multiple empirical ROC curves — doROCavg

<dl>

<dt>ROC</dt>
<dd>list of ROC curves. Each element of the list
is a data frame with pairs of (fpf, tpf) operating points.</dd>


<dt>direction</dt>
<dd>the direction over which to average<ul>
<li><code>SeSp</code> (default) The ROC curves are averaged diagonally.
 Average Se+Sp of all the input ROC curves
 for every possible Se-Sp.</li>
<li><code>Se</code> The ROC curves are averaged vertically.
 Average the sensitivity of all the input ROC curves
 for every possible specificity.</li>
<li><code>Sp</code> The ROC curves are averaged horizontally.
 Average the specificity of all the input ROC curves
 for every possible specificity.</li>
</ul></dd>

</dl>

doROCavg: Empirically average over multiple empirical ROC curves

Description

Usage

Value

Arguments