get_class

Obtain ordinal results based on log-odds (eta) and cut-offs (gamma) from MCMC
Internal function to obtain ordinal results based on log-odds (eta) and cut-offs (gamma) from MCMC.

internal

Reference-based multiple imputation of ordinal and binary responses under Bayesian
framework, as described in Wang and Liu (2022) <arXiv:2203.02771>. Methods for
missing-not-at-random include Jump-to-Reference (J2R), Copy Reference (CR), and Delta
Adjustment which can generate tipping point analysis.

Tony Wang

remiod

Reference-Based Multiple Imputation for Ordinal/Binary Response

Ying Liu

get_class function

<dl><dt>MCMC</dt>
<dd>an matrix of MCMC samples.</dd>
<dt>impvar</dt>
<dd>a name of imputation variable.</dd>
<dt>eta_name</dt>
<dd>a name of eta in mcmc samples</dd>
<dt>rev</dt>
<dd>logical. Reverse order or not.</dd>
<dt>seed</dt>
<dd>optional. A seed value for randomness.</dd></dl>

Arguments

Obtain ordinal results based on log-odds (eta) and cut-offs (gamma) from MCMC
Internal function to obtain ordinal results based on log-odds (eta) and cut-offs (gamma) from MCMC. — get_class

<dl>

<dt>MCMC</dt>
<dd>an matrix of MCMC samples.</dd>


<dt>impvar</dt>
<dd>a name of imputation variable.</dd>


<dt>eta_name</dt>
<dd>a name of eta in mcmc samples</dd>


<dt>rev</dt>
<dd>logical. Reverse order or not.</dd>


<dt>seed</dt>
<dd>optional. A seed value for randomness.</dd>

</dl>

Obtain ordinal results based on log-odds (eta) and cut-offs (gamma) from MCMC
Internal function to obtain ordinal results based on log-odds (eta) and cut-offs (gamma) from MCMC.

get_class: Obtain ordinal results based on log-odds (eta) and cut-offs (gamma) from MCMC Internal function to obtain ordinal results based on log-odds (eta) and cut-offs (gamma) from MCMC.

Description

Usage

Arguments