Introduction | A simple example | Making decisions following a pause outcome | Making adjustments following a pause outcome | Designs for continuous endpoints | Further details | References
Package: tout 1.0.3.9000
Duncan Wilson
tout: Optimal Sample Size and Progression Criteria for Three-Outcome Trials
Find the optimal decision rules (AKA progression criteria) and sample size for clinical trials with three (stop/pause/go) outcomes. Both binary and continuous endpoints can be accommodated, as can cases where an adjustment is planned following a pause outcome. For more details see Wilson et al. (2024) <doi:10.1186/s12874-024-02351-x>.
Authors:
tout_1.0.3.9000.tar.gz
tout_1.0.3.9000.zip(r-4.7-any)tout_1.0.3.9000.zip(r-4.6-any)tout_1.0.3.9000.zip(r-4.5-any)
tout_1.0.3.9000.tgz(r-4.6-any)tout_1.0.3.9000.tgz(r-4.5-any)
tout_1.0.3.9000.tar.gz(r-4.7-any)tout_1.0.3.9000.tar.gz(r-4.6-any)
tout_1.0.3.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
tout/json (API)
| # Install 'tout' in R: |
| install.packages('tout', repos = c('https://lictr.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/lictr/tout/issues
Pkgdown/docs site:https://lictr.github.io
Last updated from:5acc3c6e29. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 108 | ||
| source / vignettes | OK | 172 | ||
| linux-release | OK | 103 | ||
| macos-release | OK | 155 | ||
| macos-oldrel | OK | 212 | ||
| windows-devel | OK | 60 | ||
| windows-release | OK | 66 | ||
| windows-oldrel | OK | 69 | ||
| wasm-release | OK | 81 |
Exports:tout_design
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Plot sampling distributions of three-outcome designs | plot.tout |
| Print a tout object | print.tout |
| Find optimal sample size and progression criteria | tout_design |