Statistical modelling in GLIM4

• Comprehensive treatment of the theory of statistical modelling with generalised linear models
• Contains applications of the theory to practical problems with numerous examples
• Applications using the widely available package GLIM4 integrated in the text
• Contains three wholly new chapters on mixture and random effects models

New to this edition

• Takes into account new developments in both statistical software and statistical modelling
• Expanded discussion of statistical theory
• Three new chapters on mixture and random effects models

Readership: Ideal for graduates and research students in applied statistics and a wide range of quantitative disciplines including biology, medicine and the social sciences.

Murray Aitkin, Professor Fellow, Department of Psychology, University of Melbourne, Australia, Brian Francis, Professor of Social Statistics, Lancaster University, and John Hinde, Department of Mathematics, National University of Ireland, Galway

"The book will be appreciated by graduates, Ph-D students and professional statisticians as a tool that provides a comprehensive treatment of the statistical theory with an emphasis on application. Wide range of case studies and a gentle self-contained presentation of GLIM4 complete the monograph as an extremely useful publication." - EMS Newsletter

"...there is much practical advice, many well-worked examples, and ample GLIM4 code and output." - Thomas M. Loughin, BIOMETRICS

Preface
1: Introducing GLIM4
2: Statistical modelling and inference
3: Regression and analysis of variance
4: Binary response data
5: Multinomial and Poisson response data
6: Survival data
7: Finite mixture models
8: Random effect models
9: Variance component models
References
Index