pairwiseComparisons: Multiple Pairwise Comparison Tests

Multiple pairwise comparison tests on tidy data for one-way analysis of variance for both between-subjects and within-subjects designs. Currently, it supports only the most common types of statistical analyses and tests: parametric (Welch's and Student's t-test), nonparametric (Durbin-Conover and Dunn test), robust (Yuen’s trimmed means test), and Bayes Factor (Student's t-test).

Version: 2.0.1
Depends: R (≥ 3.6.0)
Imports: broomExtra, dplyr, dunn.test, forcats, ipmisc, PMCMRplus, purrr, rlang, stats, tidyBF (≥ 0.2.1), tidyr, utils, WRS2
Suggests: knitr, rmarkdown, spelling, testthat
Published: 2020-09-12
Author: Indrajeet Patil ORCID iD [cre, aut, cph]
Maintainer: Indrajeet Patil <patilindrajeet.science at gmail.com>
BugReports: https://github.com/IndrajeetPatil/pairwiseComparisons/issues
License: GPL-3 | file LICENSE
URL: https://indrajeetpatil.github.io/pairwiseComparisons/, https://github.com/IndrajeetPatil/pairwiseComparisons
NeedsCompilation: no
Language: en-US
Citation: pairwiseComparisons citation info
Materials: README NEWS
CRAN checks: pairwiseComparisons results

Downloads:

Reference manual: pairwiseComparisons.pdf
Package source: pairwiseComparisons_2.0.1.tar.gz
Windows binaries: r-devel: pairwiseComparisons_2.0.1.zip, r-release: pairwiseComparisons_2.0.1.zip, r-oldrel: pairwiseComparisons_2.0.1.zip
macOS binaries: r-release: pairwiseComparisons_2.0.1.tgz, r-oldrel: pairwiseComparisons_2.0.1.tgz
Old sources: pairwiseComparisons archive

Reverse dependencies:

Reverse imports: ggstatsplot

Linking:

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