Package: BCHM 1.00

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.

Authors:Nan Chen and J. Jack Lee

BCHM_1.00.tar.gz
BCHM_1.00.zip(r-4.5)BCHM_1.00.zip(r-4.4)BCHM_1.00.zip(r-4.3)
BCHM_1.00.tgz(r-4.4-any)BCHM_1.00.tgz(r-4.3-any)
BCHM_1.00.tar.gz(r-4.5-noble)BCHM_1.00.tar.gz(r-4.4-noble)
BCHM_1.00.tgz(r-4.4-emscripten)BCHM_1.00.tgz(r-4.3-emscripten)
BCHM.pdf |BCHM.html✨
BCHM/json (API)

# Install 'BCHM' in R:
install.packages('BCHM', repos = c('https://jjacklee116.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 4 scripts 282 downloads 4 exports 12 dependencies

Last updated 4 years agofrom:0e845f7f8d. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 25 2024
R-4.5-winNOTEOct 25 2024
R-4.5-linuxNOTEOct 25 2024
R-4.4-winNOTEOct 25 2024
R-4.4-macNOTEOct 25 2024
R-4.3-winNOTEOct 25 2024
R-4.3-macNOTEOct 25 2024

Exports:BCHMBCHMplot_clusterBCHMplot_post_distBCHMplot_post_value

Dependencies:clustercodacrayonevaluatehighrknitrlatticeplyrRcpprjagsxfunyaml

Using the BCHM Package

Nan Chen, J. Jack Lee

Rendered fromusing-the-BCHM-package.Rmdusingknitr::rmarkdownon Oct 25 2024.

Last update: 2019-12-20
Started: 2019-12-20