Statistical modelling in GLIM4 by Murray AitkinStatistical modelling in GLIM4 by Murray Aitkin

Statistical modelling in GLIM4

byMurray Aitkin, Brian Francis, John Hinde

Hardcover | November 18, 2005

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This new edition of the successful multi-disciplinary text iStatistical Modelling in GLIM/i takes into account new developments in both statistical software and statistical modelling. Including three new chapters on mixture and random effects models, it provides a comprehensive treatment ofthe theory of statistical modelling with generalised 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, multinomial, gamma, exponential and Weibulldistributions.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.
Murray Aitkin is at School of Mathematics and Statistics, University of Newcastle. Brian Francis is at Assistant Director, Centre for Applied Statistics, Lancaster University. John Hinde is at the National University of Ireland.
Title:Statistical modelling in GLIM4Format:HardcoverDimensions:572 pages, 9.21 × 6.14 × 1.42 inPublished:November 18, 2005Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0198524137

ISBN - 13:9780198524137

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Table of Contents

Preface1. 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

Review from previous edition `... a carefully written book containing many pearls of statistical wisdom ... this account is one that would be difficult to better.' Statistics in Medicine