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In den WarenkorbZustand: New. Walt Stroup is an Emeritus Professor of Statistics. He served on the University of Nebraska statistics faculty for over 40 years, specializing in statistical modeling and statistical design. He is a Fellow of the American Statistical Ass.
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Verlag: Taylor & Francis Inc, Portland, 2024
ISBN 10: 1498755569 ISBN 13: 9781498755566
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Hardcover. Generalized Linear Mixed Models: Modern Concepts, Methods, and Applications (2nd edition) presents an updated introduction to linear modeling using the generalized linear mixed model (GLMM) as the overarching conceptual framework. For students new to statistical modeling, this book helps them see the big picture linear modeling as broadly understood and its intimate connection with statistical design and mathematical statistics. For readers experienced in statistical practice, but new to GLMMs, the book provides a comprehensive introduction to GLMM methodology and its underlying theory.Unlike textbooks that focus on classical linear models or generalized linear models or mixed models, this book covers all of the above as members of a unified GLMM family of linear models. In addition to essential theory and methodology, this book features a rich collection of examples using SAS software to illustrate GLMM practice. This second edition is updated to reflect lessons learned and experience gained regarding best practices and modeling choices faced by GLMM practitioners. New to this edition are two chapters focusing on Bayesian methods for GLMMs.Key Features:Most statistical modeling books cover classical linear models or advanced generalized and mixed models; this book covers all members of the GLMM family classical and advanced modelsIncorporates lessons learned from experience and on-going research to provide up-to-date examples of best practicesIllustrates connections between statistical design and modeling: guidelines for translating study design into appropriate model and in-depth illustrations of how to implement these guidelines; use of GLMM methods to improve planning and designDiscusses the difference between marginal and conditional models, differences in the inference space they are intended to address and when each type of model is appropriateIn addition to likelihood-based frequentist estimation and inference, provides a brief introduction to Bayesian methods for GLMMs Generalized Linear Mixed Models: Modern Concepts, Methods and Applications (2nd edition) presents an updated introduction to linear modeling using the generalized linear mixed model (GLMM) as the overarching conceptual framework. It provides a comprehensive introduction to GLMM methodology. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Verlag: Taylor & Francis Inc, Portland, 2024
ISBN 10: 1498755569 ISBN 13: 9781498755566
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Hardcover. Generalized Linear Mixed Models: Modern Concepts, Methods, and Applications (2nd edition) presents an updated introduction to linear modeling using the generalized linear mixed model (GLMM) as the overarching conceptual framework. For students new to statistical modeling, this book helps them see the big picture linear modeling as broadly understood and its intimate connection with statistical design and mathematical statistics. For readers experienced in statistical practice, but new to GLMMs, the book provides a comprehensive introduction to GLMM methodology and its underlying theory.Unlike textbooks that focus on classical linear models or generalized linear models or mixed models, this book covers all of the above as members of a unified GLMM family of linear models. In addition to essential theory and methodology, this book features a rich collection of examples using SAS software to illustrate GLMM practice. This second edition is updated to reflect lessons learned and experience gained regarding best practices and modeling choices faced by GLMM practitioners. New to this edition are two chapters focusing on Bayesian methods for GLMMs.Key Features:Most statistical modeling books cover classical linear models or advanced generalized and mixed models; this book covers all members of the GLMM family classical and advanced modelsIncorporates lessons learned from experience and on-going research to provide up-to-date examples of best practicesIllustrates connections between statistical design and modeling: guidelines for translating study design into appropriate model and in-depth illustrations of how to implement these guidelines; use of GLMM methods to improve planning and designDiscusses the difference between marginal and conditional models, differences in the inference space they are intended to address and when each type of model is appropriateIn addition to likelihood-based frequentist estimation and inference, provides a brief introduction to Bayesian methods for GLMMs Generalized Linear Mixed Models: Modern Concepts, Methods and Applications (2nd edition) presents an updated introduction to linear modeling using the generalized linear mixed model (GLMM) as the overarching conceptual framework. It provides a comprehensive introduction to GLMM methodology. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Verlag: Taylor & Francis Inc, Portland, 2024
ISBN 10: 1498755569 ISBN 13: 9781498755566
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Hardcover. Generalized Linear Mixed Models: Modern Concepts, Methods, and Applications (2nd edition) presents an updated introduction to linear modeling using the generalized linear mixed model (GLMM) as the overarching conceptual framework. For students new to statistical modeling, this book helps them see the big picture linear modeling as broadly understood and its intimate connection with statistical design and mathematical statistics. For readers experienced in statistical practice, but new to GLMMs, the book provides a comprehensive introduction to GLMM methodology and its underlying theory.Unlike textbooks that focus on classical linear models or generalized linear models or mixed models, this book covers all of the above as members of a unified GLMM family of linear models. In addition to essential theory and methodology, this book features a rich collection of examples using SAS software to illustrate GLMM practice. This second edition is updated to reflect lessons learned and experience gained regarding best practices and modeling choices faced by GLMM practitioners. New to this edition are two chapters focusing on Bayesian methods for GLMMs.Key Features:Most statistical modeling books cover classical linear models or advanced generalized and mixed models; this book covers all members of the GLMM family classical and advanced modelsIncorporates lessons learned from experience and on-going research to provide up-to-date examples of best practicesIllustrates connections between statistical design and modeling: guidelines for translating study design into appropriate model and in-depth illustrations of how to implement these guidelines; use of GLMM methods to improve planning and designDiscusses the difference between marginal and conditional models, differences in the inference space they are intended to address and when each type of model is appropriateIn addition to likelihood-based frequentist estimation and inference, provides a brief introduction to Bayesian methods for GLMMs Generalized Linear Mixed Models: Modern Concepts, Methods and Applications (2nd edition) presents an updated introduction to linear modeling using the generalized linear mixed model (GLMM) as the overarching conceptual framework. It provides a comprehensive introduction to GLMM methodology. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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In den WarenkorbZustand: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Shows some signs of wear but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.
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In den WarenkorbZustand: Used: Good. Occasion - Bon Etat - Generalized linear mixed models. Modern concepts methods and applications (2012) - Grand Format.
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In den WarenkorbZustand: New. pp. 555 Index.
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