get_resp_mat

Identify the data matrix containing a given response variable

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

get_resp_mat function

<dl><dt>resp</dt>
<dd>character string; name of the response variable</dd>
<dt>Mlvls</dt>
<dd>named vector where the names are all column names of all data
matrices, and the values are the names of the corresponding
data matrices</dd>
<dt>outnames</dt>
<dd>character vector; names of the columns in the data matrices
that contain the response variable (or multiple columns in
case of a survival outcome)</dd></dl>

Arguments

Identify the data matrix containing a given response variable — get_resp_mat

<dl>

<dt>resp</dt>
<dd>character string; name of the response variable</dd>


<dt>Mlvls</dt>
<dd>named vector where the names are all column names of all data
matrices, and the values are the names of the corresponding
data matrices</dd>


<dt>outnames</dt>
<dd>character vector; names of the columns in the data matrices
that contain the response variable (or multiple columns in
case of a survival outcome)</dd>

</dl>

get_resp_mat: Identify the data matrix containing a given response variable

Description

Usage

Value

Arguments