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Language: English
Published by Springer (India) Private Limited, 2021
ISBN 10: 1071612816 ISBN 13: 9781071612811
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Condition: New. pp. 357 2nd Edition NO-PA16APR2015-KAP.
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Published by Springer (India) Private Limited, 2021
ISBN 10: 1071612816 ISBN 13: 9781071612811
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Language: English
Published by Springer (India) Private Limited, 2021
ISBN 10: 1071612816 ISBN 13: 9781071612811
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Taschenbuch. Condition: Neu. Linear and Generalized Linear Mixed Models and Their Applications | Jiming Jiang (u. a.) | Taschenbuch | xiv | Englisch | 2022 | Springer | EAN 9781071612842 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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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.
Buch. 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.
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Add to basketCondition: New. Concentrates on two major classes of mixed effects models, linear mixed models and generalized linear mixed modelsOffers an up-to-date account of theory and methods in the analysis of these models as well as their applications in various fields.
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Add to basketPaperback. Condition: Brand New. 271 pages. 9.00x6.00x0.63 inches. In Stock.
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