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missingHE
View on CRAN: Click
here
Download and install missingHE package within the R console
Install from CRAN:
install.packages("missingHE")
Install from Github:
library("remotes")
install_github("cran/missingHE")
Install by package version:
library("remotes")
install_version("missingHE", "1.5.0")
Attach the package and use:
library("missingHE")
Maintained by
Andrea Gabrio
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.missingHE . missingHE results . missingHE.pdf . Fitting MNAR models in missingHE . Introduction to missingHE . Longitudinal Models in missingHE . Model Customisation in missingHE . missingHE_1.5.0.tar.gz . missingHE_1.5.0.zip . missingHE_1.5.0.zip . missingHE_1.5.0.zip . missingHE_1.5.0.tgz . missingHE_1.5.0.tgz . missingHE_1.5.0.tgz . missingHE_1.5.0.tgz . missingHE archive . https://CRAN.R-project.org/package=missingHE .
First Published: 2019-05-03
Latest Update: 2023-03-21
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) , Molenberghs (2000) and Gabrio (2019) .
How to cite:
Andrea Gabrio (2019). missingHE: Missing Outcome Data in Health Economic Evaluation. R package version 1.5.0, https://cran.r-project.org/web/packages/missingHE. Accessed 05 May. 2025.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for missingHE
Functions, R codes and Examples using
the missingHE R package
Some associated functions: MenSS . PBS . anyBars . coef.missingHE . data_read_hurdle . data_read_pattern . data_read_selection . data_read_selection_long . diagnostic . fb . hurdle . isAnyArgBar . isBar . jagsresults . nobars_ . pattern . pic . plot.missingHE . ppc . print.missingHE . prior_hurdle . prior_pattern . prior_selection . prior_selection_long . run_hurdle . run_pattern . run_selection . run_selection_long . selection . selection_long . summary.missingHE . write_hurdle . write_pattern . write_selection . write_selection_long .
Some associated R codes: anyBars.R . coef.missingHE.R . data_read_hurdle.R . data_read_pattern.R . data_read_selection.R . data_read_selection_long.R . diagnostic.R . fb.R . hurdle.R . isAnyArgBar.R . isBar.R . jagsresults.R . menss-data.R . nobars_.R . pattern.R . pbs-data.R . pic.R . plot.missingHE.R . ppc.R . print.missingHE.R . prior_hurdle.R . prior_pattern.R . prior_selection.R . prior_selection_long.R . run_hurdle.R . run_pattern.R . run_selection.R . run_selection_long.R . selection.R . selection_long.R . summary.missingHE.R . write_hurdle.R . write_pattern.R . write_selection.R . write_selection_long.R . Full missingHE package functions and examples
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