Perform Bayesian Cost-Effectiveness Analysis in R.
🚀 This is the development version of the R
package BCEA
(currently on version 2.4.82). The stable version is now release 2.4.81,
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 development version (in this repo, which can be updated more quickly
and more often than the stable one) can be installed from
r-universe.dev
, using the following command
install.packages(
'BCEA',
repos = c('https://giabaio.r-universe.dev', 'https://cloud.r-project.org')
)
Alternatively, you can intall the development version using remotes
,
with the following command.
install.packages("remotes")
remotes::install_github("giabaio/BCEA")
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
.
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.