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Find the optimal graphical multiple testing procedure for confirmatory clinical trials that test several hypotheses across endpoints, doses, or subpopulations. Choose the graph maximising an explicit gain-function: a user-defined measure of trial success that scores each possible set of rejected hypotheses. Given simulated p-values, search over hypothesis weights and transition weights to maximise expected trial success. Conventional power criteria are recovered and the family-wise error rate is strongly controlled due to the search being confined to graphical procedures. Described in Spiers, Grayling, Wheeler, and Mander (2026) "Gain-function optimisation of graphical multiple testing procedures for confirmatory clinical trials" <doi:10.48550/arXiv.2609.19994>.
| Version: | 1.0.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | cli, dplyr, GA, ggplot2, ggraph, glue, igraph, mvtnorm, nloptr, purrr, Rcpp, RcppParallel (≥ 5.1.10), rlang (≥ 1.2.0), stats, tibble, tidyr, utils, vctrs, withr |
| LinkingTo: | Rcpp, RcppParallel |
| Suggests: | gMCPLite, spelling, svglite, testthat (≥ 3.0.0), vdiffr |
| Published: | 2026-10-18 |
| DOI: | 10.32614/CRAN.package.multigrain (may not be active yet) |
| Author: | Alex Spiers |
| Maintainer: | Alex Spiers <alex.d.spiers at gsk.com> |
| BugReports: | https://github.com/GSK-Biostatistics/multigrain/issues |
| License: | LGPL (≥ 3) |
| URL: | https://github.com/GSK-Biostatistics/multigrain, https://gsk-biostatistics.github.io/multigrain/ |
| NeedsCompilation: | yes |
| SystemRequirements: | GNU make |
| Language: | en-GB |
| Materials: | README, NEWS |
| CRAN checks: | multigrain results |
| Reference manual: | multigrain.html , multigrain.pdf |
| Package source: | multigrain_1.0.0.tar.gz |
| Windows binaries: | r-devel: multigrain_1.0.0.zip, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): multigrain_1.0.0.tgz, r-oldrel (arm64): multigrain_1.0.0.tgz, r-release (x86_64): multigrain_1.0.0.tgz, r-oldrel (x86_64): multigrain_1.0.0.tgz |
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