Linear and Generalized Linear Mixed Models and Their Applications
Springer-Verlag New York Inc.
978-1-0716-1284-2 (ISBN)
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.
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).
1. Linear Mixed Models: Part I.- 2. Linear Mixed Models: Part II.- 3. Generalized Linear Mixed Models: Part I.- 4. Generalized Linear Mixed Models: Part II.
Erscheinungsdatum | 25.03.2022 |
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Reihe/Serie | Springer Series in Statistics |
Zusatzinfo | 8 Illustrations, color; 5 Illustrations, black and white; XIV, 343 p. 13 illus., 8 illus. in color. |
Verlagsort | New York, NY |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Mathematik / Informatik ► Mathematik ► Analysis |
Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
Studium ► Querschnittsbereiche ► Prävention / Gesundheitsförderung | |
Schlagworte | Data Analysis • generalized linear mixed models • Linear Mixed Models • linear optimization • Mathematical Statistics • mixed model prediction • Model Selection • Public Health • random effects • Regression Analysis • restricted maximum likelihood • Small area estimation • variance components |
ISBN-10 | 1-0716-1284-0 / 1071612840 |
ISBN-13 | 978-1-0716-1284-2 / 9781071612842 |
Zustand | Neuware |
Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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