Notes:
Following an introductory overview of multivariate statistics, the nine remaining chapters each cover a multivariate technique or family of techniques. Readers learn which kinds of empirical questions are best answered by means of those techniques. Concepts and symbols are presented with a minimal use of formulas. Real-world examples illustrate the application, underlying assumptions, and interpretation of each type of analysis. Included in each chapter are a glossary of notations and concepts central to the understanding of the analysis and suggestions for further readings.
Includes bibliographical references and index.
Contents:
Introduction to multivariate statistics / Laurence G. Grimm and Paul R. Yarnold --
Multiple regression and correlation / Mark H. Licht --
Path analysis / Laura Klem --
Principal-components analysis and exploratory and confirmatory factor analysis / Fred B. Bryant and Paul R. Yarnold --
Multidimensional scaling / Loretta J. Stalans --
Analysis of cross-classified data / Willard Rogers --
Logistic regression / Raymond E. Wright --
Multivariate analysis of variance / Kevin P. Weinfurt --
Discriminant analysis / A. Pedro Duarte Silva and Antonie Stam --
Understanding meta-analysis / Joseph A. Durlak.
