DESCRIPTION

Package: BayesianMCPMod
Title: Simulate, Evaluate, and Analyze Dose Finding Trials with Bayesian
    MCPMod
Version: 1.0.2
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("Sebastian", "Bossert", , "sebastian.bossert@boehringer-ingelheim.com", role = "aut"),
    person("Steven", "Brooks", , "steven.brooks@boehringer-ingelheim.com", role = "ctb"),
    person("Jonas", "Schick", , "jonas.schick@boehringer-ingelheim.com", role = "ctb"),
    person("Gina", "Kleibrink", , "gina_marie.kleibrink@boehringer-ingelheim.com", role = "ctb")
  )
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),
    ggplot2,
    nloptr,
    RBesT,
    stats
Suggests:
    clinDR,
    data.table,
    doFuture,
    quarto,
    doRNG,
    dplyr,
    kableExtra,
    knitr,
    MCPModPack,
    reactable,
    rmarkdown,
    spelling,
    testthat (>= 3.0.0),
    tibble
VignetteBuilder: quarto
Config/testthat/edition: 3
Encoding: UTF-8
Language: en-US
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.1