Robust multivariate nonparametric tests for detection of two-sample location shift in clinical trials.

ABSTRACT: This article presents and investigates performance of a series of robust multivariate nonparametric tests for detection of location shift between two multivariate samples in randomized controlled trials. The tests are built upon robust estimators of distribution locations (medians, Hodges-Lehmann estimators, and an extended U statistic) with both unscaled and scaled versions. The nonparametric tests are robust to outliers and do not assume that the two samples are drawn from multivariate normal distributions. Bootstrap and permutation approaches are introduced for determining the p-values of the proposed test statistics. Simulation studies are conducted and numerical results are reported to examine performance of the proposed statistical tests. The numerical results demonstrate that the ro

SUBMITTER: Jiang X 

PROVIDER: S-EPMC5908204 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature