The analysis of data by statistical modelling is becoming increasingly important. This book presents both the theory of statistical modelling with generalized linear models and the application of the theory to practical problems using the widely available package GLIM. The authors have taken pains to integrate the theory with many practical examples which illustrate the value of interactive statistical modelling. Throughout the book theoretical issues of formulating and simplifying models are discussed, as are problems of validating the models by the detection of outliers and influential observations. The book arises from short courses given at the University of Lancaster's Centre for Applied Statistics, with an emphasis on practical programming in GLIM and numerous examples. A wide range of case studies is provided, using the normal, binomial, Poisson, multinomial, gamma, exponential and Weibull distributions. A feature of the book is a detailed discussion of survival analysis. Statisticians working in a wide range of fields, including biomedical and social sciences, will find this book an invaluable desktop companion to aid their statistical modelling. It will also provide a text for students meeting the ideas of statistical modelling for the first time.

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Bibliographic Details

Title: Statistical Modelling in GLIM
Publisher: Oxford University Press
Publication Date: 1989
Language: English
ISBN 10: 0198522037
ISBN 13: 9780198522034
Binding: Paperback
Condition: Good

About this title

Synopsis

This textbook is an introduction to both the theory of statistical models with general linear models and the practical implementation of these analytical techniques using a widely available computer package, GLIM (Generalized Linear Interactive Modelling). The authors fully integrate the theoretical and practical aspects, illustrating statistical principles by worked examples using GLIM's extensive interactive facilities. Statisticians working in a wide range of fields including biomedical research and the social sciences will find this an invaluable desktop companion to their statistical modelling. It also provides a hands-on guide for advanced students in these areas who may be using the techniques for the first time.

About the Author

Murray Aitkin, Department of Statistics, University of Tel Aviv. Dorothy Anderson, CSIRO Division of Mathematics and Statistics, Melbourne. Brian Francis, Lecturer at the Centre for Applied Statistics, University of Lancaster.

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