An increasing number of R packages include nonparametric tests for the interaction in two-way factorial designs. This paper briefly describes the different methods of testing and reports the resulting p-values of such tests on datasets for four types of designs: between, within, mixed, and pretest-posttest designs. Potential users are advised only to apply tests they are quite familiar with and not be guided by p-values for selecting packages and tests.
WRS2, nparLD, coin, lmPerm, perm, ez, boot, ART, ARTool, npIntFactRep, Rfit, StatMethRank, outliers, npsm, cocor
Survival, ClinicalTrials, Econometrics, ExperimentalDesign, Optimization, Psychometrics, Robust, SocialSciences, TimeSeries
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For attribution, please cite this work as
Feys, "The R Journal: Nonparametric Tests for the Interaction in Two-way Factorial Designs Using R", The R Journal, 2016
BibTeX citation
@article{RJ-2016-027,
author = {Feys, Jos},
title = {The R Journal: Nonparametric Tests for the Interaction in Two-way Factorial Designs Using R},
journal = {The R Journal},
year = {2016},
note = {https://doi.org/10.32614/RJ-2016-027},
doi = {10.32614/RJ-2016-027},
volume = {8},
issue = {1},
issn = {2073-4859},
pages = {367-378}
}