CRAN/E | missingHE

missingHE

Missing Outcome Data in Health Economic Evaluation

Installation

About

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.

Key Metrics

Version 1.5.0
R ≥ 4.2.0
Published 2023-03-21 373 days ago
Needs compilation? no
License GPL-2
CRAN checks missingHE results

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Maintainer

Maintainer

Andrea Gabrio

a.gabrio@maastrichtuniversity.nl

Authors

Andrea Gabrio

aut / cre

Material

README
Reference manual
Package source

In Views

MissingData

Vignettes

Fitting MNAR models in missingHE
Introduction to missingHE
Longitudinal Models in missingHE
Model Customisation in missingHE

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

missingHE archive

Depends

R ≥ 4.2.0

Imports

mcmcplots
ggpubr
ggmcmc
ggthemes
BCEA
ggplot2
grid
gridExtra
bayesplot
methods
R2jags
loo
coda
mcmcr

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