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Hardcover: 276 pages
Publisher: Springer; 1 edition (June 20, 1997)
Language: English
ISBN-10: 0387982183
ISBN-13: 978-0387982182
Book Description
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.
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