BayesianHybridDesign: Bayesian Hybrid Design and Analysis
Abstract
Implements Bayesian hybrid designs that incorporate historical control data into a current clinical trial. The package uses a dynamic power prior method to determine the degree of borrowing from the historical data, creating a 'hybrid' control arm. This approach is primarily designed for studies with a binary primary endpoint, such as the overall response rate (ORR). Functions are provided for design calibration, sample size calculation, power evaluation, and final analysis. Additionally, it includes functions adapted from the 'SAMprior' package (v1.1.1) by Yang et al. (2023) to support the Self-Adapting Mixture (SAM) prior framework for comparison.
Fields of Study & Subjects
Statistical Methods in Clinical Trials
Statistical Methods and Bayesian Inference
Optimal Experimental Design Methods
Publication details
- Publication date
- 6 February 2026
- Document type
- Dataset