Uses of discriminant analysis following MANOVA: Multivariate statistics for multivariate purposes

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Abstract

When a test of multiple ANOVA is found to be significant, it must be followed by other analyses before a researcher can arrive at an accurate understanding of the data set. Two possibilities for follow-up analyses include univariate ANOVA and discriminant analysis. This article presents the results of a Monte Carlo study (N = 450) wherein typical, but simple, multivariate data were analyzed by the 2 techniques. Results demonstrate that discriminant analysis is capable of showing the underlying dimensionality of the data as well as determining the contribution of individual variables to the underlying dimensions, whereas ANOVA is limited to specifying the contribution of each variable to group separation. It is argued that when researchers analyze multivariate data, primary goals become interpretation and understanding the data set. It is concluded that discriminant analysis is most suitable for this purpose. (29 ref) (PsycINFO Database Record (c) 2006 APA, all rights reserved)

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