Bayesian MCPMod (Fleischer et al. (2022) <doi:10.1002/pst.2193>) is an innovative method that improves the traditional MCPMod by systematically incorporating historical data, such as previous placebo group data. This R package offers functions for simulating, analyzing, and evaluating Bayesian MCPMod trials with normally distributed endpoints. It enables the assessment of trial designs incorporating historical data across various true dose-response relationships and sample sizes. Robust mixture prior distributions, such as those derived with the Meta-Analytic-Predictive approach (Schmidli et al. (2014) <doi:10.1111/biom.12242>), can be specified for each dose group. Resulting mixture posterior distributions are used in the Bayesian Multiple Comparison Procedure and modeling steps. The modeling step also includes a weighted model averaging approach (Pinheiro et al. (2014) <doi:10.1002/sim.6052>). Estimated dose-response relationships can be bootstrapped and visualized.
| Version: | 1.2.0 |
| Depends: | R (≥ 4.2) |
| Imports: | checkmate,DoseFinding (≥ 1.1-1),dplyr,ggplot2, methods,nloptr,RBesT, stats,tidyr |
| Suggests: | clinDR,doFuture,future.apply,kableExtra,knitr,MCPModPack,reactable,rmarkdown,spelling,testthat (≥3.0.0),tibble |
| Published: | 2025-08-28 |
| DOI: | 10.32614/CRAN.package.BayesianMCPMod |
| Author: | Boehringer Ingelheim Pharma GmbH & Co. KG [cph, fnd], Stephan Wojciekowski [aut, cre], Lars Andersen [aut], Jonas Schick [ctb], Sebastian Bossert [aut] |
| Maintainer: | Stephan Wojciekowski <stephan.wojciekowski at boehringer-ingelheim.com> |
| BugReports: | https://github.com/Boehringer-Ingelheim/BayesianMCPMod/issues |
| License: | Apache License (≥ 2) |
| URL: | https://boehringer-ingelheim.github.io/BayesianMCPMod/,https://github.com/Boehringer-Ingelheim/BayesianMCPMod |
| NeedsCompilation: | no |
| Language: | en-US |
| Citation: | BayesianMCPMod citation info |
| Materials: | README,NEWS |
| In views: | ClinicalTrials |
| CRAN checks: | BayesianMCPMod results |
| Package source: | BayesianMCPMod_1.2.0.tar.gz |
| Windows binaries: | r-devel:BayesianMCPMod_1.2.0.zip, r-release:BayesianMCPMod_1.2.0.zip, r-oldrel:BayesianMCPMod_1.2.0.zip |
| macOS binaries: | r-release (arm64):BayesianMCPMod_1.2.0.tgz, r-oldrel (arm64):BayesianMCPMod_1.2.0.tgz, r-release (x86_64):BayesianMCPMod_1.2.0.tgz, r-oldrel (x86_64):BayesianMCPMod_1.2.0.tgz |
| Old sources: | BayesianMCPMod archive |
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