Fit Bayesian Missing Cost Effectiveness Models in R.
🚀 This is the development version of the R package
missingHE (currently on version 1.6.2.1). The stable version is now
release 1.6.2, on
CRAN.
Given a individual-level partially-observed cost-effectiveness outcome data in the form of a dataframe, fits different types of Bayesian models to handle missing effect and/or cost values under different assumptions about the missing data mechanisms, assesses model performance and Markov chain Monte Carlo (MCMC) convergence, and summarises statistical and economic results based on the posterior distribution of key model parameters.
Main features of missingHE include:
- Analysis of partially-observed effects/costs data via Bayesian missingness models
- Model assessment measures/plots and MCMC convergence checks
- Posterior summaries for key model parameters and cost-effectiveness measures
- Standard cost-effectiveness measures/graphs based on model results
Install the released version from CRAN with
install.packages("missingHE")The development version (in this repo, which can be updated more quickly and more often than the stable one) can be installed using the following command
pkgs <- c("R2jags", "ggplot2", "gridExtra", "BCEA", "ggmcmc", "loo", "Rtools", "devtools", "utils")
repos <- c("https://cran.rstudio.com")
install.packages(pkgs, repos = repos, dependencies = "Depends")before installing the package using devtools:
devtools::install_github("AnGabrio/missingHE", build_vignettes = TRUE)The optional argument build_vignettes = TRUE allows to install the
vignettes of the package locally on your computer. These consist in
brief tutorials to guide the user on how to use and customise the models
in missingHE using different functions of the package. Once the
package is installed, they can be accessed using the command
utils::browseVignettes(package = "missingHE")which shows all the vignettes available for the package. Alternatively,
you can install the development version using remotes, with the
following command.
install.packages("remotes")
remotes::install_github("AnGabrio/missingHE")NB: On Windows machines, you need to install a few dependencies, including Rtools first, e.g. by running
pkgs <- c("MASS", "Rtools", "remotes")
repos <- "https://cran.rstudio.com"
install.packages(pkgs, repos = repos, dependencies = "Depends")before installing the package using remotes.
All models implemented in missingHE are written in the BUGS language
using the software JAGS, which
needs to be installed from its own repository and instructions for
installations under different OS can be found online. Once installed,
the software is called in missingHE via the R package
R2jags. Note that the
missingHE package is currently under active development and therefore
it is advisable to re-install the package directly from GitHub before
each use to ensure that you are using the most updated version.
More details on missingHE are available in our
vignettes.
Also, details about the package, including some references and links to
a pdf presentation and some posts on my own blog) are given
here.
Please submit contributions through Pull Requests, following the
contributing
guidelines.
To report issues and/or seek support, please file a new ticket in the
issue tracker.
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.