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Data from: A non-parametric maximum test for the Behrens–Fisher problem

Citation

Welz, Anke; Ruxton, Graeme D.; Neuhäuser, Markus (2019), Data from: A non-parametric maximum test for the Behrens–Fisher problem, Dryad, Dataset, https://doi.org/10.5061/dryad.8s574

Abstract

Non-normality and heteroscedasticity are common in applications. For the comparison of two samples in the non-parametric Behrens–Fisher problem, different tests have been proposed, but no single test can be recommended for all situations. Here, we propose combining two tests, the Welch t test based on ranks and the Brunner–Munzel test, within a maximum test. Simulation studies indicate that this maximum test, performed as a permutation test, controls the type I error rate and stabilizes the power. That is, it has good power characteristics for a variety of distributions, and also for unbalanced sample sizes. Compared to the single tests, the maximum test shows acceptable type I error control.

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