Linear and generalized linear mixed models and their applications / Jiming Jiang, Thuan Nguyen.

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Linear and generalized linear mixed models and their applications / Jiming Jiang, Thuan Nguyen.

Second edition.

9781071612828 electronic book
1071612824 electronic book
9781071612811
1071612816
9781071612835 (print)
1071612832
9781071612842 (print)
1071612840

New York, NY : Springer, [2021]

English

1 online resource (xiv, 343 pages) : illustrations.

10.1007/978-1-0716-1282-8 doi

QA279 .J53 2021eb

519.535

Now in its second edition, 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. It offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it discusses the latest developments and methods in the field, incorporating relevant updates since publication of the first edition. These include advances in high-dimensional linear mixed models in genome-wide association studies (GWAS), advances in inference about generalized linear mixed models with crossed random effects, new methods in mixed model prediction, mixed model selection, and mixed model diagnostics. This book is suitable for students, researchers, and practitioners who are interested in using mixed models for statistical data analysis with public health applications. It is best for graduate courses in statistics, or for those who have taken a first course in mathematical statistics, are familiar with using computers for data analysis, and have a foundational background in calculus and linear algebra.-- Provided by publisher.

Includes bibliographical references and index.

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text file

Online resource; title from digital title page (ProQuest Ebook central, viewed September 24, 2021).

Springer series in statistics.

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