I'm unsure how to calculate the effect size after applying a Wilcoxon rank-sum test. I'm using
scipy.stats.ranksums, where the outputs are
z, p. Looking at the implementation of the test, it seems
z is assumed to be normally distributed - could I just calculate Cohen's d as discussed here?
I'm confused since Wikipedia offers alternative effect sizes for these non-parametric tests, but then also, the article states that the Wilcoxon rank-sum and the Mann-Whitney-U tests are the same, while scipy clearly implements them quite differently. Unfortunately, I cannot apply the MWU test since some of my comparisons involve samples with zero variance which leads to errors with MWU but not rank-sums.