check_vars_in_data

Check that all variables in formulas are in the data

internal

used

(2020-06-09)

model_imp

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 S. Erler

JointAI

Joint Analysis and Imputation of Incomplete Data

check_vars_in_data function

<dl><dt>datanames</dt>
<dd>a character vector (of all variable names in the data)</dd>
<dt>fixed</dt>
<dd>the fixed effects formula (or list of formulas)</dd>
<dt>random</dt>
<dd>the random effects formula (or list of formulas)</dd>
<dt>auxvars</dt>
<dd>one-sided formula of auxiliary variables</dd>
<dt>timevar</dt>
<dd>a character string (name of the time variable, used in joint models)</dd></dl>

Arguments

Check that all variables in formulas are in the data — check_vars_in_data

<dl>

<dt>datanames</dt>
<dd>a character vector (of all variable names in the data)</dd>


<dt>fixed</dt>
<dd>the fixed effects formula (or list of formulas)</dd>


<dt>random</dt>
<dd>the random effects formula (or list of formulas)</dd>


<dt>auxvars</dt>
<dd>one-sided formula of auxiliary variables</dd>


<dt>timevar</dt>
<dd>a character string (name of the time variable, used in joint models)</dd>

</dl>

check_vars_in_data: Check that all variables in formulas are in the data

Description

Usage

Value

Arguments