Package: JointAI
Version: 1.0.6
Title: Joint Analysis and Imputation of Incomplete Data
Authors@R: c(person("Nicole S.", "Erler", email = "n.erler@erasmusmc.nl",
                  role = c("aut", "cre"),
                  comment = c(ORCID = "0000-0002-9370-6832")))
Description: 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'.
URL: https://nerler.github.io/JointAI/
License: GPL (>= 2)
BugReports: https://github.com/nerler/JointAI/issues/
LazyData: TRUE
RoxygenNote: 7.2.3
Imports: rjags, mcmcse, coda, rlang, future, mathjaxr, survival, MASS
SystemRequirements: JAGS (https://mcmc-jags.sourceforge.io/)
Suggests: knitr, rmarkdown, bookdown, foreign, ggplot2, ggpubr,
        testthat, covr
VignetteBuilder: knitr
Encoding: UTF-8
RdMacros: mathjaxr
Config/testthat/edition: 3
Language: en-GB
NeedsCompilation: no
Packaged: 2024-04-02 17:26:25 UTC; erler
Author: Nicole S. Erler [aut, cre] (<https://orcid.org/0000-0002-9370-6832>)
Maintainer: Nicole S. Erler <n.erler@erasmusmc.nl>
Repository: CRAN
Date/Publication: 2024-04-02 18:25:00 UTC
Built: R 4.3.3; ; 2024-04-20 01:28:48 UTC; unix
