hc_rdslope_info

Get info on the main effects in a random slope structure
for a given level and sub-model

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

hc_rdslope_info function

<dl><dt>hc_cols</dt>
<dd>list of lists (one per random effect), each containing a list
with elements "main" and "interact" that contain information
on the column number and name of the design matrix for the
random effects variables or variables interacting with them</dd>
<dt>parelmts</dt>
<dd>list (per design matrix) of indices of the regression
coefficients used for that sub-model (named with the
corresponding column name of the design matrix)</dd></dl>

Arguments

Get info on the main effects in a random slope structure
for a given level and sub-model — hc_rdslope_info

<dl>

<dt>hc_cols</dt>
<dd>list of lists (one per random effect), each containing a list
with elements "main" and "interact" that contain information
on the column number and name of the design matrix for the
random effects variables or variables interacting with them</dd>


<dt>parelmts</dt>
<dd>list (per design matrix) of indices of the regression
coefficients used for that sub-model (named with the
corresponding column name of the design matrix)</dd>

</dl>

hc_rdslope_info: Get info on the main effects in a random slope structure for a given level and sub-model

Description

Usage

Value

Arguments

Details