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Multivariate General Linear Models
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Multivariate General Linear Models



January 2012 | 224 pages | SAGE Publications, Inc
This book provides a graduate level introduction to multivariate multiple regression analysis. The book can be used as a sole text for that topic, or as a supplemental text in a course that addresses a larger number of multivariate topics.

The text is divided into seven short chapters. Apart from the introductory chapter giving an overview of multivariate multiple regression models, the content outline follows the classic steps required to solve multivariate general linear model problems:

(a) specifying the model

(b)estimating the parameters of the model

(c) establishing measures of goodness of fit of the model

(d) establishing test statistics and testing hypotheses about the model

(e) diagnosing the adequacy of the model.

 
1. Introduction and Review of Univariate General Linear Models
 
2. Specifying the Structure of the Multivariate General Linear Model
 
3. Estimating the Parameters of the Multivariate General Linear Model
 
4. Partitioning the SSCP, Measures of Strength of Association, and Test Statistics in the Multivariate General Linear Model
 
5. Testing Hypotheses in the Multivariate General Linear Model
 
6. Coding the Design Matrix and the Multivariate Analysis of Variance
 
7. The Eigenvalue Solution to the Multivariate General Linear Model: Canonical Correlation and Multivariate Test Statistics
 
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