Package: WMWssp 0.4.0
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. For details, see Brunner, E., Bathke A. C. and Konietschke, F: Rank- and Pseudo-Rank Procedures in Factorial Designs - Using R and SAS, Springer Verlag, to appear.
Authors:
WMWssp_0.4.0.tar.gz
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WMWssp_0.4.0.tgz(r-4.4-any)WMWssp_0.4.0.tgz(r-4.3-any)
WMWssp_0.4.0.tar.gz(r-4.5-noble)WMWssp_0.4.0.tar.gz(r-4.4-noble)
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WMWssp.pdf |WMWssp.html✨
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 5 years agofrom:3276393524. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 01 2024 |
R-4.5-win | OK | Nov 01 2024 |
R-4.5-linux | OK | Nov 01 2024 |
R-4.4-win | OK | Nov 01 2024 |
R-4.4-mac | OK | Nov 01 2024 |
R-4.3-win | OK | Nov 01 2024 |
R-4.3-mac | OK | Nov 01 2024 |
Exports:WMWsspWMWssp_maximizeWMWssp_minimizeWMWssp_noether
Dependencies: