Applied Multivariate Analysis

1. Front Matter

   Pages i-xxiv

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2. Introduction

   Pages 1-5

3. Vectors and Matrices

   Pages 7-78

4. Multivariate Distributions and the Linear Model

   Pages 79-184

5. Multivariate Regression Models

   Pages 185-309

6. Seemingly Unrelated Regression Models

   Pages 311-349

7. Multivariate Random and Mixed Models

   Pages 351-417

8. Discriminant and Classification Analysis

   Pages 419-443

9. Principal Component, Canonical Correlation, and Exploratory Factor Analysis

   Pages 445-514

10. Cluster Analysis and Multidimensional Scaling

    Pages 515-555

11. Structural Equation Models

    Pages 557-607

12. Back Matter

    Pages 609-693

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Univariate statistical analysis is concerned with techniques for the analysis of a single random variable. This book is about applied multivariate analysis. It was written to p- vide students and researchers with an introduction to statistical techniques for the ana- sis of continuous quantitative measurements on several random variables simultaneously. While quantitative measurements may be obtained from any population, the material in this text is primarily concerned with techniques useful for the analysis of continuous obser- tions from multivariate normal populations with linear structure. While several multivariate methods are extensions of univariate procedures, a unique feature of multivariate data an- ysis techniques is their ability to control experimental error at an exact nominal level and to provide information on the covariance structure of the data. These features tend to enhance statistical inference, making multivariate data analysis superior to univariate analysis. While in a previous edition of my textbook on multivariate analysis, I tried to precede a multivariate method with a corresponding univariate procedure when applicable, I have not taken this approach here. Instead, it is assumed that the reader has taken basic courses in multiple linear regression, analysis of variance, and experimental design. While students may be familiar with vector spaces and matrices, important results essential to multivariate analysis are reviewed in Chapter 2. I have avoided the use of calculus in this text.

• Analysis of variance
• Cluster analysis
• Factor analysis
• SAS
• analysis
• data analysis
• multidimensional scaling
• principal component analysis
• structural equation modeling

From the reviews:

"This book is more than an up-to-date textbook on multivariate analysis. It could enable SAS users to take full and informed advantage of the many options offered in the SAS procedures. For non-SAS users, the clear statement of the models should enable them to fit and interpret them with other software."

ISI Short Book Reviews, Vol. 23/2, August 2003

"This textbook is another comprehensive work on applied multivariate analysis. Basic theory and methods are reviewed and illustrated by a number of examples and practices. … The author has written a useful textbook combining most of general theory and practice of multivariate data analysis. The book is suitable to familiarize students at graduate level with main concepts and principles of multivariate analysis." (Dr. ir. M. H. J. de Bruijne, Kwantitatieve Methoden, Vol. 70B37, 2003)

"This text is on the analysis of structured data … . The author has managed to encapsulate so much in this book by giving a clear statement of each model … . This book is more than an up-to date textbook on multivariate analysis. It could enable SAS users to take full and informed advantage of the many options offered in the SAS procedures. For non-SAS users, the clear statement of the models should enable them to fit and interpret them with other software." (J. M. Juritz, Short Book Reviews, Vol. 23 (2), 2003)

"I was extremely pleased to see this book arrive. … For each subject, all important equations and distributional results are very clearly stated. … I found this book exciting, interesting and informative. The exercises are quite well chosen … . In summary, Applied Multivariate Analysis is an excellent book. If you want only one book on multivariate analysis, I would suggest this as a strong candidate. I am extremely glad that I own this book … ." (David E. Booth, Technometrics, Vol. 45 (2), May, 2003)

"This textbook provides a broad overview of the basic theory and methods of applied multivariate analysis. The presentation integrates theory and practice including both the analysis of formal linear multivariate models and exploratory date analysis techniques. … The techniques and examples discussed in the book should be helpful in the analysis of multivariate data using SAS. All programs and data sets used may be downloaded from a Web site. The book appeals to practitioners, researchers, and applied statisticians." (T. Postelnicu, Zentralblatt MATH, Vol. 1002 (2), 2003)

• Department of Education in Psychology School of Education, University of Pittsburgh, Pittsburgh

  Neil H. Timm

"This book is more than an up-to-date textbook on multivariate analysis. It could enable SAS users to take full and informed advantage of the many options offered in the SAS procedures. For non-SAS users, the clear statement of the models should enable them to fit and interpret them with other software."

ISI Short Book Reviews, Vol. 23/2, August 2003

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