expand_rd_vcov_full

Expand rd_vcov using variable names in case "full" is used

internal

Joint analysis and imputation of incomplete data in the Bayesian
framework, using (generalized) linear (mixed) models and extensions there of,
survival models, or joint models for longitudinal and survival data, as
described in Erler, Rizopoulos and Lesaffre (2021) <doi:10.18637/jss.v100.i20>.
Incomplete covariates, if present, are automatically imputed.
The package performs some preprocessing of the data and creates a 'JAGS'
model, which will then automatically be passed to 'JAGS'
<https://mcmc-jags.sourceforge.io/> with the help of
the package 'rjags'.

Nicole Erler

JointAI

Joint Analysis and Imputation of Incomplete Data

Nicole S. Erler

expand_rd_vcov_full function

<dl><dt>rd_vcov</dt>
<dd>the random effects variance covariance structure provided by
the user (<code>check_rd_vcov_list()</code> is called internally)</dd>
<dt>rd_outnam</dt>
<dd>list by grouping level of the names of the outcome variables
that have random effects on this level</dd></dl>

Arguments

Expand rd_vcov using variable names in case "full" is used — expand_rd_vcov_full

<dl>

<dt>rd_vcov</dt>
<dd>the random effects variance covariance structure provided by
the user (<code>check_rd_vcov_list()</code> is called internally)</dd>


<dt>rd_outnam</dt>
<dd>list by grouping level of the names of the outcome variables
that have random effects on this level</dd>

</dl>

expand_rd_vcov_full: Expand rd_vcov using variable names in case "full" is used

Description

Usage

Value

Arguments