Permutation Tests for Association Between Two Distance Matrices

Abstract

—Systematists and geneticists often wish to compare two pair-wise distance or similarity matrices based on different characters. Conventional correlation tests are not appropriate in such situations because of dependencies among the entries in each matrix. A broad class of permutation tests for association between distance matrices is described. Specific members of the class are discussed and compared using real and simulated data. Statistics resembling Kendall's tau and Spearman's rho are found to have desirable power and invariance properties.