Journal
JOURNAL OF EDUCATIONAL AND BEHAVIORAL STATISTICS
Volume 31, Issue 2, Pages 157-180Publisher
SAGE PUBLICATIONS INC
DOI: 10.3102/10769986031002157
Keywords
dominance analysis; multivariate association; multivariate regression; predictor importance
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Dominance analysis (DA) is a method used to compare the relative importance of predictors in multiple regression. DA determines the dominance of one predictor over another by comparing their additional R-2 contributions across all subset models. In this article DA is extended to multivariate models by identifying a minimal set of criteria for an appropriate generalization off to the case of multiple response variables. The DA results obtained by univariate regression (with each criterion separately) are analytically compared with results obtained by multivariate DA and illustrated with an example. It is shown that univariate dominance does not necessarily imply multivariate dominance (and vice versa), and it is recommended that researchers who wish to account for the correlation among the response variables use multivariate DA to determine the relative importance of predictors.
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