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Educational and Psychological Measurement
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Comparing Treatment and Control Groups on Multiple Outcomes

Robust Procedures for Testing a Directional Alternative Hypothesis

Lisa M. Lix

University of Saskatchewan, lisa.lix{at}usask.ca

Kathleen N. Deering

University of British Columbia

Rachel T. Fouladi

Simon Fraser University

Phongsack Manivong

University of Manitoba

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.

Key Words: multivariate • positive orthant hypothesis • variance heterogeneity • nonnormality • t test • likelihood ratio test

This version was published on April 1, 2009

Educational and Psychological Measurement, Vol. 69, No. 2, 198-215 (2009)
DOI: 10.1177/0013164408322027


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