BCHM: Clinical Trial Calculation Based on BCHM Design

Users can estimate the treatment effect for multiple subgroups basket trials based on the Bayesian Cluster Hierarchical Model (BCHM). In this model, a Bayesian non-parametric method is applied to dynamically calculate the number of clusters by conducting the multiple cluster classification based on subgroup outcomes. Hierarchical model is used to compute the posterior probability of treatment effect with the borrowing strength determined by the Bayesian non-parametric clustering and the similarities between subgroups. To use this package, 'JAGS' software and 'rjags' package are required, and users need to pre-install them.

Version: 1.00
Depends: R (≥ 3.5), rjags
Imports: stats, cluster, coda, knitr, crayon, plyr
Suggests: testthat
Published: 2020-06-05
DOI: 10.32614/CRAN.package.BCHM
Author: Nan Chen and J. Jack Lee
Maintainer: J. Jack Lee <jjlee at mdanderson.org>
License: LGPL-2
NeedsCompilation: no
SystemRequirements: JAGS
In views: CausalInference
CRAN checks: BCHM results


Reference manual: BCHM.pdf
Vignettes: Using the basket Package


Package source: BCHM_1.00.tar.gz
Windows binaries: r-devel: BCHM_1.00.zip, r-release: BCHM_1.00.zip, r-oldrel: BCHM_1.00.zip
macOS binaries: r-release (arm64): BCHM_1.00.tgz, r-oldrel (arm64): BCHM_1.00.tgz, r-release (x86_64): BCHM_1.00.tgz, r-oldrel (x86_64): BCHM_1.00.tgz
Old sources: BCHM archive


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