Applying Generalized Linear Models

James K. Lindsey

ISBN 10: 0387982183 / ISBN 13: 9780387982182

Editore: Springer New York, Springer New York, 1997

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Druck auf Anfrage Neuware - Printed after ordering - Applying Generalized Linear Models describes how generalized linear modelling procedures can be used for statistical modelling in many different fields, without becoming lost in problems of statistical inference. Many students, even in relatively advanced statistics courses, do not have an overview whereby they can see that the three areas - linear normal, categorical, and survival models - have much in common. The author shows the unity of many of the commonly used models and provides the reader with a taste of many different areas, such as survival models, time series, and spatial analysis. This book should appeal to applied statisticians and to scientists with a basic grounding in modern statistics. With the many exercises included at the ends of chapters, it will be an excellent text for teaching the fundamental uses of statistical modelling. The reader is assumed to have knowledge of basic statistical principles, whether from a Bayesian, frequentist, or direct likelihood point of view, and should be familiar at least with the analysis of the simpler normal linear models, regression and ANOVA. The author is professor in the biostatistics department at Limburgs University, Diepenbeek, in the social science department at the University of Liège, and in medical statistics at DeMontfort University, Leicester. He is the author of nine other books.

Codice articolo 9780387982182

Dati bibliografici

• Titolo: Applying Generalized Linear Models
• Editore: Springer New York, Springer New York
• Data di pubblicazione: 1997
• Lingua: Inglese
• ISBN 10: 0387982183
• ISBN 13: 9780387982182
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 241 L x 160 A x 20 P (millimetri) 241 millimetri di larghezza per 160 millimetri di altezza per 20 millimetri di profondità
• Peso: 582 grammi

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Riassunto

Applying Generalized Linear Models describes how generalized linear modelling procedures can be used for statistical modelling in many different fields, without becoming lost in problems of statistical inference. Many students, even in relatively advanced statistics courses, do not have an overview whereby they can see that the three areas - linear normal, categorical, and survival models - have much in common. The author shows the unity of many of the commonly used models and provides the reader with a taste of many different areas, such as survival models, time series, and spatial analysis. This book should appeal to applied statisticians and to scientists with a basic grounding in modern statistics. With the many exercises included at the ends of chapters, it will be an excellent text for teaching the fundamental uses of statistical modelling. The reader is assumed to have knowledge of basic statistical principles, whether from a Bayesian, frequentist, or direct likelihood point of view, and should be familiar at least with the analysis of the simpler normal linear models, regression and ANOVA. The author is professor in the biostatistics department at Limburgs University, Diepenbeek, in the social science department at the University of Liège, and in medical statistics at DeMontfort University, Leicester. He is the author of nine other books.

Recensione

From a review:

TECHNOMETRICS

"...one of the best applied statistical books that I have ever read."