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BayesianHybridDesign  

Bayesian Hybrid Design and Analysis
View on CRAN: Click here


Download and install BayesianHybridDesign package within the R console
Install from CRAN:
install.packages("BayesianHybridDesign")

Install from Github:
library("remotes")
install_github("cran/BayesianHybridDesign")

Install by package version:
library("remotes")
install_version("BayesianHybridDesign", "0.1.0")



Attach the package and use:
library("BayesianHybridDesign")
Maintained by
Zhaohua Lu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-02-06
Latest Update: 2026-02-06
Description:
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) <https://academic.oup.com/biometrics/article/79/4/2857/7587575> to support the Self-Adapting Mixture (SAM) prior framework for comparison.
How to cite:
Zhaohua Lu (2026). BayesianHybridDesign: Bayesian Hybrid Design and Analysis. R package version 0.1.0, https://cran.r-project.org/web/packages/BayesianHybridDesign. Accessed 04 Jul. 2026.
Previous versions and publish date:
0.1.0 (2026-02-06 21:00)
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Complete documentation for BayesianHybridDesign
Functions, R codes and Examples using the BayesianHybridDesign R package
Full BayesianHybridDesign package functions and examples
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