Package: missingHE
Type: Package
Title: Missing Outcome Data in Health Economic Evaluation
Version: 1.6.1
Authors@R: person("Andrea", "Gabrio", email = "a.gabrio@maastrichtuniversity.nl", role = c("aut", "cre"))
Description: Contains a suite of functions for health economic
        evaluations with missing outcome data. The package can fit
        different types of statistical models under a fully Bayesian
        approach using the software 'JAGS' (which should be installed
        locally and which is loaded in 'missingHE' via the 'R' package
        'R2jags'). Three classes of models can be fitted under a
        variety of missing data assumptions: selection models, pattern
        mixture models and hurdle models. In addition to model fitting,
        'missingHE' provides a set of specialised functions to assess
        model convergence and fit, and to summarise the statistical and
        economic results using different types of measures and graphs.
        The methods implemented are described in Mason (2018)
        <doi:10.1002/hec.3793>, Molenberghs (2000)
        <doi:10.1007/978-1-4419-0300-6_18> and Gabrio (2019)
        <doi:10.1002/sim.8045>.
Depends: R (>= 4.0.0)
Suggests: knitr, rmarkdown, bookdown, devtools
VignetteBuilder: knitr
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: ggpubr, ggmcmc, ggthemes, BCEA, ggplot2, bayesplot, methods,
        R2jags, loo, coda, mcmcr
Config/roxygen2/version: 8.0.0
Config/pak/sysreqs: cmake make jags libicu-dev libuv1-dev libssl-dev
Repository: https://angabrio.r-universe.dev
Date/Publication: 2026-06-01 15:15:26 UTC
RemoteUrl: https://github.com/angabrio/missinghe
RemoteRef: HEAD
RemoteSha: 1589944783da40765154e4b9e2d526350a55e84d
NeedsCompilation: no
Packaged: 2026-06-01 17:16:40 UTC; root
Author: Andrea Gabrio [aut, cre]
Maintainer: Andrea Gabrio <a.gabrio@maastrichtuniversity.nl>