UMMS Affiliation

Meyers Primary Care Institute; Department of Quantitative Health Sciences

Publication Date

4-19-2018

Document Type

Article

Disciplines

Clinical Trials | Epidemiology | Multivariate Analysis

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 robust multivariate nonparametric tests constructed from the Hodges-Lehmann estimators are more efficient than those based on medians and the extended U statistic. The permutation approach can provide a more stringent control of Type I error and is generally more powerful than the bootstrap procedure. The proposed robust nonparametric tests are applied to detect multivariate distributional difference between the intervention and control groups in the Thai Healthy Choices study and examine the intervention effect of a four-session motivational interviewing-based intervention developed in the study to reduce risk behaviors among youth living with HIV.

Keywords

Test statistics, Research errors, Permutation, HIV, Thai people, Statistical distributions, Health education and awareness, Normal distribution

Rights and Permissions

Copyright: © 2018 Jiang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

DOI of Published Version

10.1371/journal.pone.0195894

Source

PLoS One. 2018 Apr 19;13(4):e0195894. doi: 10.1371/journal.pone.0195894. eCollection 2018. Link to article on publisher's site

Journal/Book/Conference Title

PloS one

Related Resources

Link to Article in PubMed

PubMed ID

29672555

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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