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: |
1.1.2 |
Depends: |
R (≥ 3.6.0) |
Imports: |
broomExtra, dplyr, dunn.test, forcats, ipmisc (≥ 3.0.1), PMCMRplus, purrr, rlang, stats, tidyBF (≥ 0.2.1), tidyr, utils, WRS2 (≥ 1.1-0) |
Suggests: |
knitr, rmarkdown, spelling, testthat |
Published: |
2020-06-23 |
Author: |
Indrajeet Patil
[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 |