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Title: A Weighted Rank-Sum Procedure for Comparing Samples with Multiple Endpoints.
Authors: Li Q,  Liu A,  Yu K,  Yu KF
Journal: Stat Interface
Date: 2009 Jan 1
Branches: BB
PubMed ID: 19823699
PMC ID: PMC2759535
Abstract: For comparing the distribution of two samples with multiple endpoints, O'Brien (1984) proposed rank-sum-type test statistics. Huang et al. (2005) extended these statistics to the general nonparametric Behrens-Fisher hypothesis problem and obtained improved test statistics by replacing the ad hoc variance with the asymptotic variance of the rank-sum statistics. In this paper we generalize the work of O'Brien (1984) and Huang et al. (2005) and propose a weighted rank-sum statistic. We show that the weighted rank-sum statistic is asymptotically normally distributed, permitting the computation of power, p-values and confidence intervals. We further demonstrate via simulation that the weighted rank-sum statistic is efficient in controlling the type I error rate and under certain alternatives, is more powerful than the statistics of O'Brien (1984) and Huang et al.(2005).