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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 Markov Chain Monte Carlo
(MCMC) methods. 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
summarise the statistical and economic results using different types of
measures and graphs.
There are two ways of installing missingHE. A “stable”
version is packaged and binary files are available for Windows and as
source. To install the stable version on a Windows machine, run the
following command
install.packages("missingHE")which installs the package from a CRAN mirror and ensures
that install.packages() can also install the “dependencies”
(e.g. other packages that are required for missingHE to
work).
It is also possible to install missingHE using the
“development” version - this will usually be updated frequently and may
be continuously tested. On Windows machines, you need to install a few
dependencies, including Rtools first,
e.g. by running
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.
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 reinstall the package directly from
GitHub before each use to ensure that you are using the most updated
version.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.