Multivariate Analysis for the Biobehavioral and Social Sciences:A Graphical Approach outlines the essential multivariate methodsfor understanding data in the social and biobehavioral sciences.Using real-world data and the latest software applications, thebook addresses the topic in a comprehensible and hands-on manner,making complex mathematical concepts accessible to readers.
The authors promote the importance of clear, well-designedgraphics in the scientific process, with visual representationsaccompanying the presented classical multivariate statisticalmethods . The book begins with a preparatory review of univariatestatistical methods recast in matrix notation, followed by anaccessible introduction to matrix algebra. Subsequent chaptersexplore fundamental multivariate methods and related key concepts,including: *
Factor analysis and related methods *
Multivariate graphics *
Canonical correlation *
Hotelling's T-squared *
Multivariate analysis of variance (MANOVA) *
Multiple regression and the general linear model (GLM)
Each topic is introduced with a research-publication case studythat demonstrates its real-world value. Next, the question "how doyou do that?" is addressed with a complete, yet simplified,demonstration of the mathematics and concepts of the method.Finally, the authors show how the analysis of the data is performedusing Stata(R), SAS(R), and SPSS(R). The discussedapproaches are also applicable to a wide variety of modernextensions of multivariate methods as well as modern univariateregression methods. Chapters conclude with conceptual questionsabout the meaning of each method; computational questions that testthe reader's ability to carry out the procedures on simpledatasets; and data analysis questions for the use of the discussedsoftware packages.
Multivariate Analysis for the Biobehavioral and Social Sciencesis an excellent book for behavioral, health, and social sciencecourses on multivariate statistics at the graduate level. The bookalso serves as a valuable reference for professionals andresearchers in the social, behavioral, and health sciences whowould like to learn more about multivariate analysis and itsrelevant applications.