Efficient simulation-based power and sample size calculations are supported for a broad class of late-stage clinical trials. The following modules are included in the package: Adaptive designs with data-driven sample size or event count re-estimation, Adaptive designs with data-driven treatment selection, Adaptive designs with data-driven population selection, Optimal selection of a futility stopping rule, Event prediction in event-driven trials, Adaptive trials with response-adaptive randomization (experimental module), Traditional trials with multiple objectives (experimental module). Traditional trials with cluster-randomized designs (experimental module).
Version: 0.13 Depends: R (≥ 3.1.2) Imports: Rcpp (≥ 0.12.10), RcppNumerical, methods, officer, flextable, devEMF, mvtnorm, shiny, shinydashboard, shinyMatrix, foreach, parallel, doParallel, MASS, rootSolve, lme4, lmerTest, pbkrtest LinkingTo: Rcpp, RcppEigen, RcppNumerical Suggests: testthat, doRNG Published: 2023-08-28 DOI: 10.32614/CRAN.package.MedianaDesigner Author: Alex Dmitrienko [aut, cre] Maintainer: Alex Dmitrienko <admitrienko at mediana.us> BugReports: https://github.com/medianasoft/MedianaDesigner/issues License: GPL-3 URL: https://github.com/medianasoft/MedianaDesigner NeedsCompilation: yes Materials: ChangeLog CRAN checks: MedianaDesigner results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=MedianaDesigner to link to this page.
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