pistar_by_chain

Compute the Mean Conditional Probability of Correct Classification, by True Outcome Across all Subjects for each MCMC Chain

Use frequentist and Bayesian methods to estimate parameters from a
binary outcome misclassification model. These methods correct for the problem
of "label switching" by assuming that the sum of outcome sensitivity and
specificity is at least 1. A description of the analysis methods is
available in Hochstedler and Wells (2023) <doi:10.48550/arXiv.2303.10215>.

Kimberly Hochstedler

COMBO

Correcting Misclassified Binary Outcomes in Association Studies

Kimberly Hochstedler Webb

pistar_by_chain function

<dl><dt>n_chains</dt>
<dd>An integer specifying the number of MCMC chains to compute over.</dd>
<dt>chains_list</dt>
<dd>A numeric list containing the samples from <code>n_chains</code>
MCMC chains.</dd>
<dt>Z</dt>
<dd>A numeric design matrix.</dd>
<dt>n</dt>
<dd>An integer value specifying the number of observations in the sample.
This value should be equal to the number of rows of the design matrix, <code>Z</code>.</dd>
<dt>n_cat</dt>
<dd>The number of categorical values that the true outcome, <code>Y</code>,
and the observed outcome, <code>Y*</code> can take.</dd></dl>

Arguments

Compute the Mean Conditional Probability of Correct Classification, by True Outcome Across all Subjects for each MCMC Chain — pistar_by_chain

<dl>

<dt>n_chains</dt>
<dd>An integer specifying the number of MCMC chains to compute over.</dd>


<dt>chains_list</dt>
<dd>A numeric list containing the samples from <code>n_chains</code>
MCMC chains.</dd>


<dt>Z</dt>
<dd>A numeric design matrix.</dd>


<dt>n</dt>
<dd>An integer value specifying the number of observations in the sample.
This value should be equal to the number of rows of the design matrix, <code>Z</code>.</dd>


<dt>n_cat</dt>
<dd>The number of categorical values that the true outcome, <code>Y</code>,
and the observed outcome, <code>Y*</code> can take.</dd>

</dl>

pistar_by_chain: Compute the Mean Conditional Probability of Correct Classification, by True Outcome Across all Subjects for each MCMC Chain

Description

Usage

Value

Arguments