In recent years, an enormous amount of work has been done in the field of multivariate analysis, and a growing number of social, behavioral, and biological professionals have come to rely on these techniques for their research needs. Multivariate Analysis: Methods and Applications is an in-depth guide to multivariate methods. Employing a minimum of mathematical theory, it uses real data from a wide range of disciplines to illustrate not only ideas and applications, but also the subtleties of these methods. Special coverage of important topics not found in other general multivariate texts includes: multidimensional scaling, cross-classified categorical data, latent structure analysis, and linear structural relations (LISREL). A technical appendix reviews linear algebra and matrices and contains some distributional results dealing with the multivariate normal, multinomial, and Wishart distributions.