Package: JointAI
Version: 1.1.0
Title: Joint Analysis and Imputation of Incomplete Data
Authors@R: c(person("Nicole S.", "Erler", email = "n.s.erler@umcutrecht.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: 7.3.3
Roxygen: list(old_usage = TRUE, markdown = TRUE)
Imports: rjags, mcmcse, coda, rlang, future, mathjaxr, survival, MASS
SystemRequirements: JAGS (https://mcmc-jags.sourceforge.io/)
Suggests: knitr, rmarkdown, bookdown, foreign, ggplot2, corrplot,
        ggpubr, svglite, testthat, covr
VignetteBuilder: knitr
Encoding: UTF-8
RdMacros: mathjaxr
Config/testthat/edition: 3
Language: en-GB
Config/pak/sysreqs: cmake libfftw3-dev make jags libuv1-dev
Repository: https://nerler.r-universe.dev
Date/Publication: 2026-02-22 17:10:10 UTC
RemoteUrl: https://github.com/nerler/jointai
RemoteRef: HEAD
RemoteSha: ab46e5a5cd0ac998140f92af67619845a3d10509
NeedsCompilation: no
Packaged: 2026-06-22 10:00:22 UTC; root
Author: Nicole S. Erler [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-9370-6832>)
Maintainer: Nicole S. Erler <n.s.erler@umcutrecht.nl>