JointAI: Joint Analysis and Imputation of Incomplete Data

Provides joint analysis and imputation of (generalized) linear and cumulative logit regression models, (generalized) linear and cumulative logit mixed models and parametric (Weibull) as well as Cox proportional hazards survival 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 and allows to export imputed values.

Package details

AuthorNicole S. Erler [aut, cre] (<https://orcid.org/0000-0002-9370-6832>)
MaintainerNicole S. Erler <[email protected]>
LicenseGPL (>= 2)
Version0.5.0
URL https://nerler.github.io/JointAI
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("JointAI")

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JointAI documentation built on March 8, 2019, 5:18 p.m.