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WMWssp

R package for sample size calculation for the Wilcoxon-Mann-Whitney test.

https://github.com/happma/wmwssp

Science Score: 49.0%

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Keywords

nonparametric-statistic optimal-design r rstats sample-size-calculation wilcoxon-mann-whitney-test

Keywords from Contributors

high-dimensional-data longitudinal-data
Last synced: 6 months ago · JSON representation

Repository

R package for sample size calculation for the Wilcoxon-Mann-Whitney test.

Basic Info
  • Host: GitHub
  • Owner: happma
  • Language: R
  • Default Branch: master
  • Homepage:
  • Size: 37.1 KB
Statistics
  • Stars: 2
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Topics
nonparametric-statistic optimal-design r rstats sample-size-calculation wilcoxon-mann-whitney-test
Created almost 8 years ago · Last pushed about 1 year ago
Metadata Files
Readme Changelog

README.md

WMWssp 0.5.3

CRANstatus DOI

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 for example [1] or [2].

To install the current development version:

``` r

install devtools package if it's not already

if (!requireNamespace("devtools", quietly = TRUE)) { install.packages("devtools") }

install package

devtools::install_github("happma/WMWssp") library(WMWssp) ```

To calculate the sample size we need prior information from one group. Let us call this group reference group. Based on this reference group, we can create artifical data according to an interpretable effect. Note that we have to specify, how many subjects should be assigned to the first and how many to the second group. ``` r

Prior information for the reference group

x <- c(315,375,356,374,412,418,445,403,431,410,391,475,379)

generate data for treatment group based on a shift effect

y <- x - 20

calculate sample size

ssp <- WMWssp(x, y, alpha = 0.05, power = 0.8, t = 1/2) summary(ssp) It is also possible to vary the allocation rate to even further reduce the sample size. But for almost all situations, a balanced design will be optimal or close to optimal, see [2] or [3]. r

calculate optimal allocation rate t

ssp <- WMWssp_minimize(x, y, alpha = 0.05, power = 0.8) summary(ssp) ```

References

[1] Brunner, E., Bathke A. C. and Konietschke, F: Rank- and Pseudo-Rank Procedures in Factorial Designs - Using R and SAS, Springer Verlag, to appear,

[2] Happ, M., Bathke, A. C., & Brunner, E. (2019). Optimal sample size planning for the Wilcoxon‐Mann‐Whitney test. Statistics in medicine, 38(3), 363-375.

[3] Bürkner, P‐C, Doebler, P, Holling, H. Optimal design of the Wilcoxon–Mann–Whitney‐test. Biom J. 2017; 59( 1): 25‐ 40.

Owner

  • Name: happma
  • Login: happma
  • Kind: user

PHD in statistics | data scientist | actuary

GitHub Events

Total
  • Push event: 7
Last Year
  • Push event: 7

Committers

Last synced: 8 months ago

All Time
  • Total Commits: 30
  • Total Committers: 4
  • Avg Commits per committer: 7.5
  • Development Distribution Score (DDS): 0.533
Past Year
  • Commits: 7
  • Committers: 1
  • Avg Commits per committer: 7.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Martin Happ m****p@a****t 14
Happ Martin b****1@i****t 8
Martin Happ h****a@M****x 7
Martin Happ m****p@a****t 1
Committer Domains (Top 20 + Academic)
aon.at: 2 mini-von-martin.fritz.box: 1 is.sbg.ac.at: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 1
  • Total pull requests: 0
  • Average time to close issues: about 6 hours
  • Average time to close pull requests: N/A
  • Total issue authors: 1
  • Total pull request authors: 0
  • Average comments per issue: 2.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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Top Authors
Issue Authors
  • IreneSchmidtmann (1)
Pull Request Authors
Top Labels
Issue Labels
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Packages

  • Total packages: 1
  • Total downloads:
    • cran 341 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 6
  • Total maintainers: 1
cran.r-project.org: WMWssp

Wilcoxon-Mann-Whitney Sample Size Planning

  • Versions: 6
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 341 Last month
Rankings
Stargazers count: 28.5%
Forks count: 28.8%
Dependent packages count: 29.8%
Dependent repos count: 35.5%
Average: 38.3%
Downloads: 69.1%
Maintainers (1)
martin.happ@aon.at
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.4.0 depends
  • testthat * suggests
.github/workflows/rhub.yaml actions
  • r-hub/actions/checkout v1 composite
  • r-hub/actions/platform-info v1 composite
  • r-hub/actions/run-check v1 composite
  • r-hub/actions/setup v1 composite
  • r-hub/actions/setup-deps v1 composite
  • r-hub/actions/setup-r v1 composite