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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: | 1.0.1 |
| Depends: | R (≥ 4.2) |
| Imports: | checkmate, DoseFinding (≥ 1.1-1), ggplot2, nloptr, RBesT, stats |
| Suggests: | clinDR, dplyr, knitr, rmarkdown, spelling, testthat (≥ 3.0.0) |
| Published: | 2024-04-05 |
| DOI: | 10.32614/CRAN.package.BayesianMCPMod |
| Author: | Boehringer Ingelheim Pharma GmbH & Co. KG [cph, fnd], Stephan Wojciekowski [aut, cre], Lars Andersen [aut], Steven Brooks [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://github.com/Boehringer-Ingelheim/BayesianMCPMod |
| NeedsCompilation: | no |
| Language: | en-US |
| Citation: | BayesianMCPMod citation info |
| Materials: | README NEWS |
| CRAN checks: | BayesianMCPMod results |
| Reference manual: | BayesianMCPMod.pdf |
| Vignettes: |
Simulation Example of Bayesian MCPMod for Continuous Data Analysis Example of Bayesian MCPMod for Continuous Data |
| Package source: | BayesianMCPMod_1.0.1.tar.gz |
| Windows binaries: | r-devel: BayesianMCPMod_1.0.1.zip, r-release: BayesianMCPMod_1.0.1.zip, r-oldrel: BayesianMCPMod_1.0.1.zip |
| macOS binaries: | r-release (arm64): BayesianMCPMod_1.0.1.tgz, r-oldrel (arm64): BayesianMCPMod_1.0.1.tgz, r-release (x86_64): BayesianMCPMod_1.0.1.tgz, r-oldrel (x86_64): BayesianMCPMod_1.0.1.tgz |
| Old sources: | BayesianMCPMod archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.