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: 1.1.0 Depends: R (≥ 4.2) Imports: checkmate, DoseFinding (≥ 1.1-1), future.apply, ggplot2, methods, nloptr, RBesT, stats Suggests: clinDR, data.table, doFuture, doRNG, dplyr, future, kableExtra, knitr, MCPModPack, reactable, rmarkdown, spelling, testthat (≥ 3.0.0), tibble, tidyr Published: 2025-03-07 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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=BayesianMCPMod to link to this page.
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