Multivariate General Linear Models

Nonfiction, Science & Nature, Mathematics, Statistics, Reference & Language, Reference, Research
Cover of the book Multivariate General Linear Models by Richard F. Haase, SAGE Publications
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Richard F. Haase ISBN: 9781483342115
Publisher: SAGE Publications Publication: November 23, 2011
Imprint: SAGE Publications, Inc Language: English
Author: Richard F. Haase
ISBN: 9781483342115
Publisher: SAGE Publications
Publication: November 23, 2011
Imprint: SAGE Publications, Inc
Language: English

Multivariate General Linear Models is an integrated introduction to multivariate multiple regression analysis (MMR) and multivariate analysis of variance (MANOVA). Beginning with an overview of the univariate general linear model, this volume defines the key steps in analyzing linear model data, and introduces multivariate linear model analysis as a generalization of the univariate model. The author focuses on multivariate measures of association for four common multivariate test statistics, presents a flexible method for testing hypotheses on models, and emphasizes the multivariate procedures attributable to Wilks, Pillai, Hotelling, and Roy. The volume concludes with a discussion of canonical correlation analysis that is shown to subsume all the multivariate procedures discussed in previous chapters. The analyses are illustrated throughout the text with three running examples drawing from several disciples, including personnel psychology, anthropology, environmental epidemiology, and neuropsychology.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Multivariate General Linear Models is an integrated introduction to multivariate multiple regression analysis (MMR) and multivariate analysis of variance (MANOVA). Beginning with an overview of the univariate general linear model, this volume defines the key steps in analyzing linear model data, and introduces multivariate linear model analysis as a generalization of the univariate model. The author focuses on multivariate measures of association for four common multivariate test statistics, presents a flexible method for testing hypotheses on models, and emphasizes the multivariate procedures attributable to Wilks, Pillai, Hotelling, and Roy. The volume concludes with a discussion of canonical correlation analysis that is shown to subsume all the multivariate procedures discussed in previous chapters. The analyses are illustrated throughout the text with three running examples drawing from several disciples, including personnel psychology, anthropology, environmental epidemiology, and neuropsychology.

More books from SAGE Publications

Cover of the book Essential Statistical Analysis "In Focus" by Richard F. Haase
Cover of the book "Sit and Get" Won't Grow Dendrites by Richard F. Haase
Cover of the book Sociological Theory by Richard F. Haase
Cover of the book Cultural Proficiency by Richard F. Haase
Cover of the book Teaching Literacy to Learners with Dyslexia by Richard F. Haase
Cover of the book Colonializing Agriculture by Richard F. Haase
Cover of the book Encyclopedia of Educational Theory and Philosophy by Richard F. Haase
Cover of the book Wellbeing from Birth by Richard F. Haase
Cover of the book A Critical Companion to Early Childhood by Richard F. Haase
Cover of the book Researching Social Life by Richard F. Haase
Cover of the book Concepts in World Politics by Richard F. Haase
Cover of the book Common Core for the Not-So-Common Learner, Grades 6-12 by Richard F. Haase
Cover of the book Uncovering Student Thinking About Mathematics in the Common Core, High School by Richard F. Haase
Cover of the book Children's Mathematics by Richard F. Haase
Cover of the book Uncovering Student Thinking About Mathematics in the Common Core, Grades 3-5 by Richard F. Haase
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy