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

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

 
By: Jiming Jiang

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Year: 2007
Pages: 271
Language: English
Published: Springer

This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models. 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 includes 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.

 

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