Two-Sample Tests

Abstract

This chapter introduces permutation methods for two-sample tests. Included in this chapter are six example analyses illustrating computation of exact permutation probability values for two-sample tests, calculation of measures of effect size for two-sample tests, the effect of extreme values on conventional and permutation two-sample tests, exact and Monte Carlo permutation procedures for two-sample tests, application of permutation methods to two-sample rank-score data, and analysis of two-sample multivariate data. Included in this chapter are permutation versions of Student’s two-sample t test, the Wilcoxon–Mann–Whitney two-sample rank-sum test, Hotelling’s multivariate T2 test for two independent samples, and a permutation-based alternative for the four conventional measures of effect size for two-sample tests: Cohen’s \(\hat{d}\), Pearson’s r2, Kelley’s 𝜖2, and Hays’ \(\hat{\omega }^{2}\).