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bhmbasket  

Bayesian Hierarchical Models for Basket Trials
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("bhmbasket", "0.9.5")



Attach the package and use:
library("bhmbasket")
Maintained by
Stephan Wojciekowski
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-02-15
Latest Update: 2022-02-14
Description:
Provides functions for the evaluation of basket trial designs with binary endpoints. Operating characteristics of a basket trial design are assessed by simulating trial data according to scenarios, analyzing the data with Bayesian hierarchical models (BHMs), and assessing decision probabilities on stratum and trial-level based on Go / No-go decision making. The package is build for high flexibility regarding decision rules, number of interim analyses, number of strata, and recruitment. The BHMs proposed by Berry et al. (2013) and Neuenschwander et al. (2016) , as well as a model that combines both approaches are implemented. Functions are provided to implement Bayesian decision rules as for example proposed by Fisch et al. (2015) . In addition, posterior point estimates (mean/median) and credible intervals for response rates and some model parameters can be calculated. For simulated trial data, bias and mean squared errors of posterior point estimates for response rates can be provided.
How to cite:
Stephan Wojciekowski (2021). bhmbasket: Bayesian Hierarchical Models for Basket Trials. R package version 0.9.5, https://cran.r-project.org/web/packages/bhmbasket. Accessed 22 Sep. 2026.
Previous versions and publish date:
(2026-07-09 07:21), 0.9.1 (2021-02-15 11:50), 0.9.2 (2021-04-07 19:20), 0.9.3 (2021-10-11 19:10), 0.9.4 (2022-01-18 10:22), 0.9.5 (2022-02-14 15:40), 1.0.0 (2026-02-21 07:11)
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Complete documentation for bhmbasket
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