Oxford Statistical Science
2 primary works
Book 4
Statistical Modelling in GLIM
by Murray Aitkin, etc., Dorothy Anderson, Brian Francis, and John Hinde
Published 12 January 1989
An introduction to both the theory of statistical models and the practical implementation of these techniques in the analysis of data using the package GLIM 3, the statistical package for Generalized Linear Interactive Modelling, developed by the Working Party on Statistical Computing of the Royal Statistical Society. The authors have aimed to integrate both the theoretical and practical aspects, thus all the statistical principles which are discussed are illustrated by worked examples using GLIM's interactive facilities. A full description of the use of GLIM 3 for model fitting is given with detailed discussions of many examples. This book was written from 1982-1987 as part of an Economic and Social Research Council research programme at the Centre for Applied Statistics in the analysis of complex social data, which supported Dorothy Anderson and John Hinde. There are several way this book can be used. It is written in sequence which is intended to be appropriate for intensive courses. Chapter 1 gives a gentle introduction to GLIM 3 for novices and chapter 2 a general introduction to the principles of statistical modelling, with two simple examples.
This chapter also develops the necessary theory of maximum likelihood estimation and likelihood ratio testing. Chapter 3 discusses the normal model, chapter 4 binomial data, chapter 5 multinomial and Poisson data and chapter 6 survival data. This work should be of value to statisticians working in a wide range of fields including biomedical research and the social sciences as well as providing a "hands on" guide for students in these areas using these techniques for the first time.
This chapter also develops the necessary theory of maximum likelihood estimation and likelihood ratio testing. Chapter 3 discusses the normal model, chapter 4 binomial data, chapter 5 multinomial and Poisson data and chapter 6 survival data. This work should be of value to statisticians working in a wide range of fields including biomedical research and the social sciences as well as providing a "hands on" guide for students in these areas using these techniques for the first time.
Book 32
Statistical modelling in GLIM4
by Murray Aitkin, Brian Francis, and John Hinde
Published 24 March 2005
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.
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.