Multivariate data analysis in empirical research. A look on the bright side.
The interpretive benefits of employing multivariate analysis methods on experimental data with more than one dependent variable are described heuristically and illustrated on a set of data from a simply designed experiment in physiological psychology. Multivariate analysis of variance (MANOVA) is performed on the 9 dependent variables contained in the sample data and on the four composites derived from a principal components analysis (PCA) of the variability of the nine. A linear discriminant analysis (LDA) is conducted following both MANOVA results, and 5 methods of determining the "important" dependent variables in the experimental-control group difference are presented and discussed in terms of the data at hand.
D000704:Analysis of Variance; D000818:Animals; D004032:Diet; D010437:Peptic Ulcer / Q000517:prevention & control; D011603:Psychophysiology; D051381:Rats; D012107:Research Design