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Linear and Generalized Linear Mixed Models and Their Applications (Springer Series in Statistics) - Softcover
- PublisherSpringer
- Publication date2022
- ISBN 10 1071612840
- ISBN 13 9781071612842
- BindingPaperback
- LanguageEnglish
- Edition number2
- Number of pages357
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Linear and Generalized Linear Mixed Models and Their Applications (Springer Series in Statistics)
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Linear and Generalized Linear Mixed Models and Their Applications (Springer Series in Statistics)
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Linear and Generalized Linear Mixed Models and Their Applications (Springer Series in Statistics)
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Linear and Generalized Linear Mixed Models and Their Applications
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Springer-Verlag New York Inc., 2022
ISBN 10: 1071612840
ISBN 13: 9781071612842
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Linear and Generalized Linear Mixed Models and Their Applications
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Springer New York Mrz 2022, 2022
ISBN 10: 1071612840
ISBN 13: 9781071612842
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Taschenbuch
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 360 pp. Englisch. Seller Inventory # 9781071612842
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Linear and Generalized Linear Mixed Models and Their Applications
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Springer, Berlin|Springer New York|National Science Foundation|Springer, 2022
ISBN 10: 1071612840
ISBN 13: 9781071612842
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models. Furthermore, it includes recently developed methods, such as mixed model diagnostics, mixed model selection, and jackknife method in the con. Seller Inventory # 577693019
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Linear and Generalized Linear Mixed Models and Their Applications
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Springer New York, Springer US, 2022
ISBN 10: 1071612840
ISBN 13: 9781071612842
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Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9781071612842
Quantity: 1 available