check_rd_vcov

Check / create the random effects variance-covariance matrix specification

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

check_rd_vcov function

<dl><dt>rd_vcov</dt>
<dd>variance covariance specification provided by the user</dd>
<dt>nranef</dt>
<dd>list by level with named vectors of number of random effects
per variable (obtained by <code>get_nranef()</code>)</dd></dl>

Arguments

Check / create the random effects variance-covariance matrix specification — check_rd_vcov

<dl>

<dt>rd_vcov</dt>
<dd>variance covariance specification provided by the user</dd>


<dt>nranef</dt>
<dd>list by level with named vectors of number of random effects
per variable (obtained by <code>get_nranef()</code>)</dd>

</dl>

check_rd_vcov: Check / create the random effects variance-covariance matrix specification

Description

Usage

Arguments