Abstract
Although it is simple to determine whether multivariate group differences are statistically significant or not, such differences are often difficult to interpret. This article is about common principal components analysis as a tool for the exploratory investigation of multivariate group differences and its relation to traditional statistical methods and structural equation modeling. Real data are used for illustration.
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