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Updated: Oct 8, 2025

An R-Based Landscape Validation of a Competing Risk Model

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

BayesCTDesign: An R Package for Bayesian Trial Design Using Historical Control Data.

Barry S Eggleston¹, Joseph G Ibrahim², Becky McNeil¹

¹RTI International.

Journal of Statistical Software

|January 3, 2022

Summary

The BayesCTDesign R package facilitates Bayesian clinical trial design for two-arm trials, incorporating historical data when available for robust analysis and power estimation.

Keywords:

Bayesian statistics R clinical trials historical controls power prior

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Area of Science:

Biostatistics
Clinical Trial Design
Statistical Software

Background:

Bayesian methods offer a flexible framework for clinical trial design.
Utilizing historical control data can enhance trial efficiency and power.
Standard trial designs may not fully leverage available prior information.

Purpose of the Study:

Introduce the R package BayesCTDesign for Bayesian two-arm randomized clinical trial design.
Provide tools for trial design with and without historical control data.
Facilitate the study of trial characteristics through simulation.

Main Methods:

The BayesCTDesign package offers historic_sim() and simple_sim() functions for scenario-based simulations.
Supports various outcome types: Gaussian, Poisson, Bernoulli, Weibull, Lognormal, and Piecewise Exponential (pwe).
Estimates power via simulation by comparing 95% credible intervals to null values.

Main Results:

The package enables the study of trial characteristics under user-defined scenarios.
Provides print() and plot() methods for summarizing simulated trial results.
Demonstrates the application of Bayesian trial design principles with practical examples.

Conclusions:

BayesCTDesign is a valuable R package for Bayesian two-arm clinical trial design.
It supports the integration of historical data, enhancing statistical power.
The package offers a user-friendly interface for simulation and analysis.