censor_data

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

censor_data function

<dl><dt>n_obs</dt>
<dd>An integer representing the number of observations to simulate.</dd>
<dt>first_reads_all</dt>
<dd>Used for binary methods. A logical which forces method
1 to have a result for every observation</dd>
<dt>n_method_subset</dt>
<dd>Used for binary methods. An integer defining how
many methods to select at random to produce a result for each observation</dd>
<dt>n_method</dt>
<dd>An integer representing the number of methods to simulate.</dd></dl>

Arguments

Censor data randomly rowwise — censor_data

<dl>

<dt>n_obs</dt>
<dd>An integer representing the number of observations to simulate.</dd>


<dt>first_reads_all</dt>
<dd>Used for binary methods. A logical which forces method
1 to have a result for every observation</dd>


<dt>n_method_subset</dt>
<dd>Used for binary methods. An integer defining how
many methods to select at random to produce a result for each observation</dd>


<dt>n_method</dt>
<dd>An integer representing the number of methods to simulate.</dd>

</dl>

censor_data: Censor data randomly rowwise

Description

Usage

Arguments