This new edition of the successful multi-disciplinary text Statistical Modelling in GLIM 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 of the 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 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.
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
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