JointAI: Joint Analysis and Imputation of Incomplete Data

Provides joint analysis and imputation of linear regression models, generalized linear regression models or linear mixed models with incomplete (covariate) data in the Bayesian framework. The package performs some preprocessing of the data and creates a 'JAGS' model, which will then automatically be passed to 'JAGS' <http://mcmc-jags.sourceforge.net> with the help of the package 'rjags'. It also provides summary and plotting functions for the output.

Version: 0.2.0
Depends: rjags (≥ 4-6)
Imports: MASS, mcmcse, coda
Suggests: knitr, rmarkdown, mice, foreign
Published: 2018-07-05
Author: Nicole S. Erler [aut, cre]
Maintainer: Nicole S. Erler <n.erler at erasmusmc.nl>
BugReports: https://github.com/nerler/JointAI
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/nerler/JointAI
NeedsCompilation: no
SystemRequirements: JAGS (http://mcmc-jags.sourceforge.net)
Materials: README NEWS
CRAN checks: JointAI results

Downloads:

Reference manual: JointAI.pdf
Package source: JointAI_0.2.0.tar.gz
Windows binaries: r-devel: JointAI_0.2.0.zip, r-release: JointAI_0.2.0.zip, r-oldrel: JointAI_0.2.0.zip
OS X binaries: r-release: JointAI_0.2.0.tgz, r-oldrel: JointAI_0.2.0.tgz
Old sources: JointAI archive

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