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Linear and Generalized Linear Mixed Models and Their Applications Springer Series in Statistics



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R3 476.00
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This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models, and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. The book offers a systemat... Read more
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Features
Author Jiming Jiang
Format Hardcover
ISBN 9780387479415
Publisher Springer
Manufacturer Springer
Description

This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models, and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. The book offers a systematic approach to inference about non-Gaussian linear mixed models.

Furthermore, it has included recently developed methods, such as mixed model diagnostics, mixed model selection, and jackknife method in the context of mixed models. The book is aimed at students, researchers and other practitioners who are interested in using mixed models for statistical data analysis.

The book is suitable for a course in a M.S. program in statistics, provided that the section of further results and technical notes in each of the first four chapters is skipped. If these four sections are included, the book may be used for a course in a Ph. D. program in statistics. A first course in mathematical statistics, the ability to use computers for data analysis, and familiarity with calculus and linear algebra are prerequisites.

Additional statistical courses such as regression analysis and a good knowledge about matrices would be helpful.



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Linear and Generalized Linear Mixed Models and Their Applications Springer Series in Statistics is manufactured by Springer. You can browse more Springer products on PriceCheck.

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