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.
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.
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