Package: BayesianQDM
Type: Package
Title: Bayesian Quantitative Decision-Making Framework for Binary,
        Continuous and Time-to-Event Endpoints
Version: 1.0.0
Authors@R: c(
    person(given  = "Gosuke",
           family = "Homma",
           role   = c("aut", "cre"),
           email  = "my.name.is.gosuke@gmail.com"),
    person(given  = "Yusuke",
           family = "Yamaguchi",
           role   = c("aut")))
Description: Bayesian quantitative decision-making for proof-of-concept
    clinical trials with Go, NoGo and Gray decisions. A study is specified by
    its sample sizes, conjugate prior distributions, external data borrowed
    through power priors, a concurrent, external, hypothetical or fixed
    control group, and a decision criterion based on the posterior or
    posterior predictive probability of the treatment effect. The package
    computes the decision for observed data, the operating characteristics
    of a design under scenarios for the true parameters, the decision
    thresholds that control the probabilities of false Go and false NoGo
    decisions, and the observed data that lead to each decision. One
    or two binary endpoints (Beta-binomial and Dirichlet-multinomial
    models), one or two continuous endpoints (Normal-Inverse-chi-squared and
    Normal-Inverse-Wishart models) and one time-to-event endpoint evaluated
    by the milestone survival probability or the hazard ratio (exponential
    model with Gamma priors) are supported, with larger or smaller effects
    as favorable. The posterior distributions have closed forms, so
    Markov chain Monte Carlo (MCMC) sampling is not needed; the
    probabilities are computed from closed-form distribution functions, by
    exact summation, numerical integration, a moment-matching approximation
    or Monte Carlo simulation, with the main computations in C++. See Kang,
    Yamaguchi, and Han (2026) <doi:10.1080/10543406.2026.2655410> for the
    methodological framework.
License: GPL (>= 2)
Encoding: UTF-8
Language: en-US
Imports: ggplot2 (>= 3.4.0), grDevices, Rcpp, stats
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, spelling, testthat (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
URL: https://gosukehommaEX.github.io/BayesianQDM/,
        https://github.com/gosukehommaEX/BayesianQDM
BugReports: https://github.com/gosukehommaEX/BayesianQDM/issues
Config/roxygen2/version: 8.0.0
NeedsCompilation: yes
Packaged: 2026-10-30 09:43:42 UTC; i_lik
Author: Gosuke Homma [aut, cre],
  Yusuke Yamaguchi [aut]
Maintainer: Gosuke Homma <my.name.is.gosuke@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-30 10:20:19 UTC
