Springer Series in Statistics

Linear and Generalized Linear Mixed Models and Their Applications

Authors: Jiang, Jiming, Nguyen, Thuan

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  • Features exercises and real examples throughout, to ensure retention of information
  • Offers an up-to-date account of theory and methods in the analysis of these models as well as their applications in various fields
  • Provides a comprehensive coverage of linear mixed models and generalized linear mixed models
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  • ISBN 978-1-0716-1282-8
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Hardcover $119.99
price for USA in USD
  • ISBN 978-1-0716-1281-1
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About this book

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.

About the authors

Jiming Jiang is Professor of Statistics and a former Director of Statistical Laboratory at the University of California, Davis. He is a prominent researcher in the fields of mixed effects models, small area estimation, model selection, and statistical genetics. He is the author of Large Sample Techniques for Statistics (Springer 2010), Robust Mixed Model Analysis (2019), Asymptotic Analysis of Mixed Effects Models: Theory, Applications, and Open Problems (2017), and The Fence Methods (with T. Nguyen, 2016). He has been editorial board member of The Annals of Statistics and Journal of the American Statistical Association, among others. He is a Fellow of the American Association for the Advancement of Science, the American Statistical Association, and the Institute of Mathematical Statistics; an elected member of the International Statistical Institute; and a Yangtze River Scholar (Chaired Professor, 2017-2020).

Thuan Nguyen is Associate Professor of Biostatistics in the School of Public Health at Oregon Health & Science University, where she teaches and advises graduate students. She is an active researcher in the field of biostatistics, specializing in the analysis of longitudinal data and statistical genetics, as well as small area estimation. She is the coauthor of The Fence Methods (with J. Jiang 2016).



Table of contents (4 chapters)

Table of contents (4 chapters)

Buy this book

eBook $89.00
price for USA in USD
  • ISBN 978-1-0716-1282-8
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $119.99
price for USA in USD
  • ISBN 978-1-0716-1281-1
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
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Bibliographic Information

Bibliographic Information
Book Title
Linear and Generalized Linear Mixed Models and Their Applications
Authors
Series Title
Springer Series in Statistics
Copyright
2021
Publisher
Springer-Verlag New York
Copyright Holder
Springer Science+Business Media, LLC, part of Springer Nature
eBook ISBN
978-1-0716-1282-8
DOI
10.1007/978-1-0716-1282-8
Hardcover ISBN
978-1-0716-1281-1
Series ISSN
0172-7397
Edition Number
2
Number of Pages
XIV, 343
Number of Illustrations
5 b/w illustrations, 8 illustrations in colour
Topics