get_missinfo

This function returns a <code>data.frame</code> or a <code>list</code> of
<code>data.frame</code>s per grouping level. Each of the <code>data.frames</code>
has columns <code>variable</code>, <code>#NA</code> (number of missing values) and
<code>%NA</code> (proportion of missing values in percent).

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_missinfo function

<dl><dt>object</dt>
<dd>object inheriting from class JointAI</dd></dl>

Arguments

Obtain a summary of the missing values involved in an object of class JointAI — get_missinfo

<dl>

<dt>object</dt>
<dd>object inheriting from class JointAI</dd>

</dl>

get_missinfo: Obtain a summary of the missing values involved in an object of class JointAI

Description

Usage

Arguments

Examples