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Zusatztext ...there is much practical advice, many well-worked examples, and ample GLIM4 code and output. Klappentext 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. Zusammenfassung Ideal for graduates and research students in applied statistics and a wide range of quantitative disciplines, this text gives a comprehensive treatment of the theory of statistical modelling with generalised linear models with an emphasis on applications of the theory to practical problems, using the widely available package GLIM4. Inhaltsverzeichnis 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
