ERIC Number: EJ750874
Record Type: Journal
Publication Date: 2006
Pages: 24
Abstractor: Author
ISBN: N/A
ISSN: ISSN-1076-9986
EISSN: N/A
Comparing Predictors in Multivariate Regression Models: An Extension of Dominance Analysis
Azen, Razia; Budescu, David V.
Journal of Educational and Behavioral Statistics, v31 n2 p157-180 Sum 2006
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[squared] 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 of R[squared] 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.
Descriptors: Multivariate Analysis, Predictor Variables, Multiple Regression Analysis, Comparative Analysis
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A