Two-sample quantile tests under general conditions

Abstract

Summary A simple, nonparametric two-sample test for equality of a given collection of quantiles is developed which can be applied to a variety of empirical distribution functions, including the Kaplan‐Meier estimator, a self-consistent estimator for doubly-censored data and an estimator for repeated measures data. The null hypothesis tested is that the quantiles are equal but other aspects of the distributions may diVer between the two samples. This procedure can also be applied to quantile testing in group sequential clinical trials with staggered patient entry. A simple simulation study demonstrates that the moderate sample size properties of this procedure are reasonable.