Package: BayesianMCPMod
Title: Simulate, Evaluate, and Analyze Dose Finding Trials with
        Bayesian MCPMod
Version: 1.2.0
Authors@R: c(
    person("Boehringer Ingelheim Pharma GmbH & Co. KG", role = c("cph", "fnd")),
    person("Stephan", "Wojciekowski", , "stephan.wojciekowski@boehringer-ingelheim.com", role = c("aut", "cre")),
    person("Lars", "Andersen", , "lars.andersen@boehringer-ingelheim.com", role = "aut"),
    person("Jonas", "Schick", , "jonas.schick@boehringer-ingelheim.com", role = "ctb"),
    person("Sebastian", "Bossert", , "sebastian.bossert@boehringer-ingelheim.com", role = "aut")
  )
Description: 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.
License: Apache License (>= 2)
URL: https://boehringer-ingelheim.github.io/BayesianMCPMod/,
        https://github.com/Boehringer-Ingelheim/BayesianMCPMod
BugReports: https://github.com/Boehringer-Ingelheim/BayesianMCPMod/issues
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
VignetteBuilder: knitr
Config/testthat/edition: 3
Encoding: UTF-8
Language: en-US
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2025-08-28 20:53:16 UTC; wojcie
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@boehringer-ingelheim.com>
Repository: CRAN
Date/Publication: 2025-08-28 21:20:02 UTC
Built: R 4.6.0; ; 2025-12-17 05:27:33 UTC; windows
