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Biometrika 1999 86(4):909-921; doi:10.1093/biomet/86.4.909
© 1999 by Biometrika Trust
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Two-sample quantile tests under general conditions

MR Kosorok

Department of Statistics, Biostatistics & Medical Informatics, University of Wisconsin, K6/428 Clinical Science Center, 600 Highland Avenue, Madison, Wisconsin 53792, USA E-mail: kosorok@biostat.wisc.edu

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 differ 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.

Key Words: doubly-censored data; empirical distribution function; group sequential methods; Kaplan-Meier estimator; kernel density estimation; minimum dispersion statistic; nonparametric methods


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