Comparing Treatment and Control Groups on Multiple Outcomes

Author:

Lix Lisa M.1,Deering Kathleen N.2,Fouladi Rachel T.3,Manivong Phongsack4

Affiliation:

1. University of Saskatchewan,

2. University of British Columbia

3. Simon Fraser University

4. University of Manitoba

Abstract

This study considers the problem of testing the difference between treatment and control groups on m ≥ 2 measures when it is assumed a priori that the treatment group will perform better than the control group on all measures. Two procedures are investigated that do not rest on the assumptions of covariance homogeneity or multivariate normality: a likelihood ratio test based on a bootstrap critical value and a composite step-down procedure based on trimmed means. Type I error rates of both procedures are insensitive to assumption violations. Procedures that test a directional alternative hypothesis can be substantially more powerful than a procedure that tests a nondirectional hypothesis for certain configurations of the population mean vectors. The differences in average power of the investigated procedures are a function of the configuration of the population means, the magnitude of correlation among the outcome measures, and the shape of the population distribution.

Publisher

SAGE Publications

Subject

Applied Mathematics,Applied Psychology,Developmental and Educational Psychology,Education

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. On Statistical Significance of Discriminant Function Coefficients;Journal of Modern Applied Statistical Methods;2020-05-22

2. Testing multiple outcomes in repeated measures designs.;Psychological Methods;2010

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