A Graphical Approach

Multivariate Analysis for the Biobehavioral and Social Sciences:
A Graphical Approach outlines the essential multivariate methods
for understanding data in the social and biobehavioral sciences.
Using real-world data and the latest software applications, the
book 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-designed
graphics in the scientific process, with visual representations
accompanying the presented classical multivariate statistical
methods . The book begins with a preparatory review of univariate
statistical methods recast in matrix notation, followed by an
accessible introduction to matrix algebra. Subsequent chapters
explore fundamental multivariate methods and related key concepts,
including:

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  Factor analysis and related methods

  
  


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  Multivariate graphics

  
  


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  Canonical correlation

  
  


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  Hotelling's T-squared

  
  


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  Multivariate analysis of variance (MANOVA)

  
  


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  Multiple regression and the general linear model (GLM)

  
  

Each topic is introduced with a research-publication case study
that demonstrates its real-world value. Next, the question "how do
you 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 performed
using Stata®, SAS®, and SPSS®. The discussed
approaches are also applicable to a wide variety of modern
extensions of multivariate methods as well as modern univariate
regression methods. Chapters conclude with conceptual questions
about the meaning of each method; computational questions that test
the reader's ability to carry out the procedures on simple
datasets; and data analysis questions for the use of the discussed
software packages.

Multivariate Analysis for the Biobehavioral and Social Sciences
is an excellent book for behavioral, health, and social science
courses on multivariate statistics at the graduate level. The book
also serves as a valuable reference for professionals and
researchers in the social, behavioral, and health sciences who
would like to learn more about multivariate analysis and its
relevant applications.