ABSTRACT
All seven of the multivariate methods [i.e., multiple regression (MR), analysis of covariance (ANCOVA), multivariate analysis of variance (MANOVA), discriminant function analysis (DFA), logistic regression (LR), canonical correlation (CC), principal components analysis and factor analysis (PCA-FA)] covered in this book can analyze multiple variables, taking into account other variables in the analysis. All the methods involve some form of linear combination, with some methods (e.g., DFA, CC, PCA, FA) having more than one of these. Most of the methods (i.e., MANOVA, DFA, CC, PCA, and FA) involve eigenvalues that are variances of the linear combinations.
