Perform Bayesian Cost-Effectiveness Analysis in R.
This is the development version of the R
package BCEA
.
🚀 Version 2.4-6 available now! Check out the release notes here (changes are incremental with respect to the previous "stable" version, 2.4-5
. Version 2.4-6
is now the official release also available from CRAN
). This repo will contain continuous changes and improvements before the next official release on CRAN.
Given the results of a Bayesian model (possibly based on MCMC) in the form of simulations from the posterior distributions of suitable variables of costs and clinical benefits for two or more interventions, produces a health economic evaluation. Compares one of the interventions (the "reference") to the others ("comparators").
Main features of BCEA
include:
- Cost-effectiveness analysis plots, such as CE planes and CEAC
- Summary statistics and tables
- EVPPI calculations and plots
Install the released version from CRAN with
install.packages("BCEA")
The stable version (which can be updated more quickly) can be installed using this GitHub repository. On Windows machines, you need to install a few dependencies, including Rtools first, e.g. by running
pkgs <- c("MASS", "Rtools", "remotes")
repos <- c("https://cran.rstudio.com", "https://inla.r-inla-download.org/R/stable/")
install.packages(pkgs, repos=repos, dependencies = "Depends")
before installing the package using remotes
:
remotes::install_github("giabaio/BCEA")
Under Linux or MacOS, it is sufficient to install the package via remotes
:
install.packages("remotes")
remotes::install_github("giabaio/BCEA")
Examples of using specific functions and their different arguments are given in these articles:
- Get Started
- Set
bcea()
Parameters: Constructor and Setters - Cost-Effectiveness Acceptability Curve Plots
- Cost-Effectiveness Efficiency Frontier
- Risk Aversion Analysis
- Expected Incremental Benefit Plot
- Paired vs Multiple Comparisons
The pkgdown
site is here.
More details on BCEA
are available in our book Bayesian Cost-Effectiveness Analysis with the R Package BCEA (published in the UseR! Springer series). 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.