Package: WMWssp 0.5.3
WMWssp: Wilcoxon-Mann-Whitney Sample Size Planning
Calculates the minimal sample size for the Wilcoxon-Mann-Whitney test that is needed for a given power and two sided type I error rate. The method works for metric data with and without ties, count data, ordered categorical data, and even dichotomous data. But data is needed for the reference group to generate synthetic data for the treatment group based on a relevant effect. See Happ et al. (2019, <doi:10.1002/sim.7983>) for details.
Authors:
WMWssp_0.5.3.tar.gz
WMWssp_0.5.3.zip(r-4.7)WMWssp_0.5.3.zip(r-4.6)WMWssp_0.5.3.zip(r-4.5)
WMWssp_0.5.3.tgz(r-4.6-any)WMWssp_0.5.3.tgz(r-4.5-any)
WMWssp_0.5.3.tar.gz(r-4.7-any)WMWssp_0.5.3.tar.gz(r-4.6-any)
WMWssp_0.5.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
WMWssp/json (API)
NEWS
| # Install 'WMWssp' in R: |
| install.packages('WMWssp', repos = c('https://happma.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/happma/wmwssp/issues
nonparametric-statisticoptimal-designsample-size-calculationwilcoxon-mann-whitney-test
Last updated from:4d6c1184a5. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 105 | ||
| source / vignettes | OK | 126 | ||
| linux-release-x86_64 | OK | 101 | ||
| macos-release-arm64 | OK | 121 | ||
| macos-oldrel-arm64 | OK | 147 | ||
| windows-devel | OK | 61 | ||
| windows-release | OK | 67 | ||
| windows-oldrel | OK | 85 | ||
| wasm-release | OK | 83 |
Exports:WMWsspWMWssp_maximizeWMWssp_minimizeWMWssp_noether
Dependencies:
