# Applied Multivariate Analysis

Springer Science & Business Media, Jun 19, 2002 - Mathematics - 695 pages
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.

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### Contents

 Introduction 1 2 9 xix 32 xxiii 53 Multivariate Distributions and the Linear Model 79 Multivariate Regression Models 185 Seemingly Unrelated Regression Models 311 310 Multivariate Random and Mixed Models 351
 Discriminant and Classification Analysis 419 418 Principal Component Canonical Correlation and Exploratory 445 Structural Equation Models 557 556 Appendix 609 References 625 Author Index 667 Subject Index 675 Copyright

### About the author (2002)

"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