define_disease_state

Define the True disease state of a simulated sample

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

define_disease_state function

<dl><dt>D</dt>
<dd>Optional binary vector representing the true classification of
each observation.</dd>
<dt>n_obs</dt>
<dd>An integer representing the number of observations to simulate.</dd>
<dt>prev</dt>
<dd>A value between 0-1 which represents the proportion of
"positive" results in the target population.</dd></dl>

Arguments

Define the True disease state of a simulated sample — define_disease_state

<dl>

<dt>D</dt>
<dd>Optional binary vector representing the true classification of
each observation.</dd>


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


<dt>prev</dt>
<dd>A value between 0-1 which represents the proportion of
"positive" results in the target population.</dd>

</dl>

define_disease_state: Define the True disease state of a simulated sample

Description

Usage

Value

Arguments