A non-parametric maximum test for the Behrens–Fisher problem
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.
Citation
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
Publication
Journal of Statistical Computation and Simulation
Status
Peer reviewed
ISSN
0094-9655Type
Journal article
Collections
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