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: |
3.1.3 |
| Depends: |
R (≥ 3.6.0) |
| Imports: |
BayesFactor, dplyr, ipmisc (≥ 5.0.2), parameters (≥ 0.11.0), PMCMRplus, purrr, rlang, stats, WRS2 |
| Suggests: |
knitr, rmarkdown, spelling, testthat |
| Published: |
2021-02-03 |
| Author: |
Indrajeet Patil 
[cre, aut, cph] (@patilindrajeets) |
| 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 |