plot.boot_ML

<code>plot.boot_ML()</code> creates univariate plots of bootstrap results from <code>boot_ML()</code>.

Produce maximum likelihood estimates of common accuracy statistics
for multiple measurement methods when a gold standard is not available. An R
implementation of the expectation maximization algorithms described in Zhou et
al. (2011) <doi:10.1002/9780470906514> with additional functions for creating
simulated data and visualizing results. Supports binary, ordinal, and
continuous measurement methods.

Corie Drake

emery

Accuracy Statistic Estimation for Imperfect Gold Standards

plot.boot_ML function

<dl><dt>x</dt>
<dd>a result created by calling <code>boot_ML</code> on a <code>MultiMethodMLEstimate</code> object.</dd>
<dt>probs</dt>
<dd>a vector of distribution quantile values to indicate with vertical lines.</dd>
<dt>...</dt>
<dd>additional arguments.</dd></dl>

Arguments

Plot univariate distributions of bootstrapped ML estimates — plot.boot_ML

<dl>

<dt>x</dt>
<dd>a result created by calling <code>boot_ML</code> on a <code>MultiMethodMLEstimate</code> object.</dd>


<dt>probs</dt>
<dd>a vector of distribution quantile values to indicate with vertical lines.</dd>


<dt>...</dt>
<dd>additional arguments.</dd>

</dl>

plot.boot_ML: Plot univariate distributions of bootstrapped ML estimates

Description

Usage

Value

Arguments