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

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.