A Heteroscedastic Analog of the Wilcoxon–Mann–Whitney Test When There Is A Covariate

Abstract

A basic method for comparing two independent groups is in terms of the probability that a randomly sampled observation from the first group is less than a randomly sampled observation from the second group. The Wilcoxon–Mann–Whitney test is based on an estimate of this probability, but it uses an incorrect estimate of the standard error when the distributions differ. Numerous methods have been derived that are aimed at dealing with this issue. The goal here is to suggest a method for estimating this probability, given the value of a covariate. A well-known quantile regression estimator provides a way of dealing with this issue. The paper reports simulation results on how well this method performs.