Combination-Based Permutation Tests: Equipower Property and Power Behaviour in Presence of Correlation

Multivariate combination-based permutation tests have been widely used in many complex problems. In this paper we focus on the equipower property, derived directly from the finite sample consistency property, and we analyze the impact of the dependency structure on the combined tests. At first, we consider the finite sample consistency property which assumes sample sizes are fixed (and possibly small) and considers on each subject a large number of informative variables. Moreover, since permutation test statistics do not require to be standardized, we need not assuming that data are homoscedastic in the alternative. The equipower property is then derived from these two notions: consider the unconditional permutation power of a test statistic T for fixed sample sizes, with V ≥ 2 independent and identically distributed variables and fixed effect δ, calculated in two ways: i) by considering two V-dimensional samples sized m 1 and m 2, respectively; ii) by considering two unidimensional samples sized n 1 = Vm 1 and n 2 = Vm 2, respectively. Since the unconditional power essentially depends on the non-centrality induced by T, and two ways are provided with exactly the same likelihood and the same non-centrality, we show that they are provided with the same power function, at least approximately. As regards both investigating the equipower property and the power behaviour in presence of correlation we performed an extensive simulation study.