Linear and Generalized Linear Mixed Models and Their Applications

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Synopsis

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.

Book details

Edition:
2nd ed. 2021
Series:
Springer Series in Statistics
Author:
Jiming Jiang, Thuan Nguyen
ISBN:
9781071612828
Related ISBNs:
9781071612811
Publisher:
Springer New York
Pages:
N/A
Reading age:
Not specified
Includes images:
Yes
Date of addition:
2021-04-22
Usage restrictions:
Copyright
Copyright date:
2021
Copyright by:
Springer Science+Business Media, LLC, part of Springer Nature 
Adult content:
No
Language:
English
Categories:
Mathematics and Statistics, Medicine, Nonfiction