aravamu2 / bayesct

Adaptive Bayesian Clinical Trial

bayesCT - Tool for Simulation and Analysis of Adaptive Bayesian Clinical Trials

Authors: Thevaa Chandereng, Donald Musgrove, Tarek Haddad, Graeme Hickey, Timothy Hanson and Theodore Lystig

Overview

bayesCT is a R package for simulation and analysis of adaptive Bayesian randomized controlled trials under a range of trial designs and outcome types. Currently, it supports Gaussian, binomial, and time-to-event. The bayesCT package website is available here. Please note this package is still under development.

Installation

Prior to analyzing your data, the R package needs to be installed. The easiest way to install bayesCT is through CRAN:

install.packages("bayesCT")

There are other additional ways to download bayesCT. The first option is most useful if want to download a specific version of bayesCT (which can be found at https://github.com/thevaachandereng/bayesCT/releases):

devtools::install_github("thevaachandereng/[email protected]")

# or 

devtools::install_version("bayesCT", version = "x.x.x", repos = "http://cran.us.r-project.org")

The second option is to download through GitHub:

devtools::install_github("thevaachandereng/bayesCT")

After successful installation, the package must be loaded into the working space:

library(bayesCT)

Usage

See the vignettes for usage instructions and example.

Code of Conduct

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.

License

bayesCT is available under the open source GNU General Public License, version 3.