Abstract
We demonstrate how many classical rank tests, such as the Wilcoxon–Mann–Whitney, Kruskal–Wallis, and Friedman test, can be embedded in a statistical modeling framework and how the method can be used to construct new rank tests. In addition to hypothesis testing, the method allows for estimating effect sizes with an informative interpretation, resulting in a better understanding of the data. Supplementary materials for this article are available online.
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