BayesianMCPMod: Simulate, Evaluate, and Analyze Dose Finding Trials with Bayesian MCPMod

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

Documentation:

Reference manual: BayesianMCPMod.pdf
Vignettes: Simulation Example of Bayesian MCPMod for Continuous Data
Analysis Example of Bayesian MCPMod for Continuous Data

Downloads:

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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