BayesianHybridDesign: Bayesian Hybrid Design and Analysis
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.
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.1) |
| Imports: |
assertthat, checkmate, doParallel, foreach, ggplot2, Metrics, parallel, RBesT |
| Suggests: |
broom, knitr, purrr, rmarkdown, rstanarm, scales, testthat (≥ 3.0.0), tidyr, tools |
| Published: |
2026-02-06 |
| DOI: |
10.32614/CRAN.package.BayesianHybridDesign (may not be active yet) |
| Author: |
Philip He [aut, cph],
Zhaohua Lu [aut, cre, cph] |
| Maintainer: |
Zhaohua Lu <zhaohua.lu at gmail.com> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
BayesianHybridDesign results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=BayesianHybridDesign
to link to this page.