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Description

Simulation and Analysis of Adaptive Bayesian Clinical Trials.

Simulation and analysis of Bayesian adaptive clinical trials for binomial, Gaussian, and time-to-event data types, incorporates historical data and allows early stopping for futility or early success. The package uses novel and efficient Monte Carlo methods for estimating Bayesian posterior probabilities, evaluation of loss to follow up, and imputation of incomplete data. The package has the functionality for dynamically incorporating historical data into the analysis via the power prior or non-informative priors.

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

Build Status CRAN_Status_Badge Download_Badge License: GPL v3 contributions welcome Build status codecov Binder lifecycle

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.

Metadata

Version

0.99.3

License

Unknown

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