A non-parametric maximum test for the Behrens–Fisher problem
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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.
Welz , A , Ruxton , G D & Neuhäuser , M 2018 , ' A non-parametric maximum test for the Behrens–Fisher problem ' Journal of Statistical Computation and Simulation , vol. 88 , no. 7 , pp. 1336-1347 . https://doi.org/10.1080/00949655.2018.1431236
Journal of Statistical Computation and Simulation
© 2018, Informa UK Ltd, trading as Taylor & Francis Group. This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1080/00949655.2018.1431236
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