Statistical Modelling in GLIM4 / Edition 2

by Murray Aitkin, Brian Francis, John Hinde

Overview

This new edition of the successful multi-disciplinary text Statistical Modelling in GLIM takes into account new developments in both statistical software and statistical modeling. Including three new chapters on mixture and random effects models, it provides a comprehensive treatment of the theory of statistical modeling with generalized linear models with an emphasis on applications to practical problems and an expanded discussion of statistical theory. A wide range of case studies is also provided, using the normal, binomial Poisson, multinominal, gamma, exponential and Weibull distributions. This book is ideal for graduates and research students in applied statistics and a wide range of quantitative disciplines, including biology, medicine, and the social sciences. Professional statisticians at all levels will also find it an invaluable desktop companion.

Product Details

ISBN-13:	9780198524137
Publisher:	Oxford University Press
Publication date:	06/02/2005
Series:	Oxford Statistical Science Series , #32
Edition description:	REV
Pages:	572
Product dimensions:	9.30(w) x 6.30(h) x 1.50(d)

About the Author

University of Lancaster

CSIRO Division of Mathematics and Statistics, Melbourne

Table of Contents

1. Introducing GLIM42. Statistical Modelling and Inference3. Regression and Analysis of Variance4. Binary Response Data5. Multinomial and Poisson Response Data6. Survival Data7. Finite Mixture Models8. Random Effect Models9. Variance Component ModelsReferencesIndex

Editorial Reviews

"Well organized... Professional statisticians at all levels will also find it an invaluable desktop companion."—Technometrics

From the Publisher

Introduction to both the theory of statistical models and the practical implementation of these analytical techniques using a widely available computer package, GLIM3 (Generalized Linear Interactive Modelling). The authors integrate the theoretical and practical aspects, illustrating statistical principles by worked examples. Accessible to advanced students and statisticians in biomedical research and the social sciences. Annotation c. Book News, Inc., Portland, OR (booknews.com)

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