Missing Cost Effectiveness Models

Performs Bayesian cost-effectiveness analysis with missing outcome data. Three classes of models can be fitted under a variety of missing data assumptions: selection models, pattern mixture models and hurdle models. The package allows to assess model convergence and summarise the statistical and economic results using different types of measures and graphs. The methods implemented are described in Mason (2018) , Molenberghs (2000) and Gabrio (2019) .


Reference manual

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install.packages("missingHE")

1.6.2 by Andrea Gabrio, 2 days ago


https://github.com/AnGabrio/missingHE


Report a bug at https://github.com/AnGabrio/missingHE/issues/


Browse source code at https://github.com/cran/missingHE


Authors: Andrea Gabrio [aut, cre, cph] (ORCID:


Documentation:   PDF Manual  


GPL-2 license


Imports ggpubr, ggmcmc, ggthemes, BCEA, ggplot2, bayesplot, methods, R2jags, loo, coda, mcmcr

Suggests knitr, rmarkdown, bookdown, devtools


See at CRAN