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Raykov and Marcoulides' new text focuses on the core multivariate statistics topics which are of fundamental relevance for its understanding.
The authors believe that a good grasp of the fundamentals better prepares students for more advanced applied pursuits. This relatively non-technical introduction to the basic concepts of applied multivariate analysis places particular emphasis on the topics that are most critical to those in the behavioral, social, and educational sciences. To make the material as accessible as possible, the authors emphasize where appropriate analogies between the already familiar univariate statistics and multivariate statistics. Mathematical formulas are used only for definitional meaning rather than as proofs. SPSS and SAS are used throughout the book and some chapters feature Mplus.
The book specific website accompanying the book provides all the data used in the text. The Appendix explains the data files and its variables. The software code (for SAS and Mplus) or the sequence of the menu option selection (for SPSS) is also presented on the website and discussed at appropriate places in the book. The authors' goal is to better prepare students for more advanced studies of this exciting subject. This book is distinguished by its use of latent variable modeling in later chapters to address multivariate analysis questions that are of special interest to behavioral and social science students. These include the study of group mean differences on unobserved (latent) variables, testing of latent structure, and some introductory aspects of missing data analysis and longitudinal data modeling.
This book will appeal to graduate and advanced undergraduate students and researchers in the behavioral and social sciences and education who have limited familiarity with multivariate statistics. An introductory statistics course with exposure to regression analysis is a recommended prerequisite, as is some familiarity with SPSS and SAS.