Abstract
In psychological research, comparisons between two groups are frequently made to demonstrate that one group exhibits higher values. Although Welch’s unequal variances t-test has become the preferred parametric test for this purpose, surpassing Student’s equal variances t-test, the Wilcoxon–Mann–Whitney test remains the predominant nonparametric approach despite sharing similar limitations with Student’s t-test. Specifically, the Wilcoxon–Mann–Whitney test is associated with strong, unrealistic assumptions and lacks robustness when these assumptions are violated. The Brunner–Munzel test overcomes these limitations, featuring fewer assumptions, akin to Welch’s t-test in the parametric domain, and has thus been recommended over the Wilcoxon–Mann–Whitney test. However, the Brunner–Munzel test is currently unavailable in user-friendly statistical software, such as SPSS, making it inaccessible to many researchers. In this paper, I introduce the bmtest module for jamovi, a freely available user-friendly software. By making the Brunner–Munzel test accessible to a wide range of researchers, the bmtest module has the potential to improve nonparametric statistical analysis in psychology and other disciplines.
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