PMCMR: Calculate Pairwise Multiple Comparisons of Mean Rank Sums

The Kruskal and Wallis one-way analysis of variance by ranks or van der Waerden's normal score test can be employed, if the data do not meet the assumptions for one-way ANOVA. Provided that significant differences were detected by the omnibus test, one may be interested in applying post-hoc tests for pairwise multiple comparisons (such as Nemenyi's test, Dunn's test, Conover's test, van der Waerden's test). Similarly, one-way ANOVA with repeated measures that is also referred to as ANOVA with unreplicated block design can also be conducted via the Friedman-Test or the Quade-test. The consequent post-hoc pairwise multiple comparison tests according to Nemenyi, Conover and Quade are also provided in this package. Finally Durbin's test for a two-way balanced incomplete block design (BIBD) is also given in this package.

Version: 4.1
Depends: R (≥ 3.0.0), stats, base
Suggests: multcompView, xtable, graphics
Published: 2016-01-06
Author: Thorsten Pohlert
Maintainer: Thorsten Pohlert <thorsten.pohlert at gmx.de>
License: GPL (≥ 3)
NeedsCompilation: no
Citation: PMCMR citation info
Materials: NEWS
CRAN checks: PMCMR results

Downloads:

Reference manual: PMCMR.pdf
Vignettes: Pairwise Multiple Comparison of Mean Rank Sums
Package source: PMCMR_4.1.tar.gz
Windows binaries: r-devel: PMCMR_4.1.zip, r-release: PMCMR_4.1.zip, r-oldrel: PMCMR_4.1.zip
OS X El Capitan binaries: r-release: PMCMR_4.1.tgz
OS X Mavericks binaries: r-oldrel: PMCMR_4.1.tgz
Old sources: PMCMR archive

Reverse dependencies:

Reverse imports: easyDes, jmv
Reverse suggests: mlr

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