Negative Binomial Regression
This second edition of Hilbe's Negative Binomial Regression is a substantial enhancement to the popular first edition. The only text devoted entirely to the negative binomial model and its many variations, nearly every model discussed in the literature is addressed. The theoretical and distributional background of each model is discussed, together with examples of their construction, application, interpretation and evaluation. Complete Stata and R codes are provided throughout the text, with additional code (plus SAS), derivations and data provided on the book's website. Written for the practising researcher, the text begins with an examination of risk and rate ratios, and of the estimating algorithms used to model count data. The book then gives an in-depth analysis of Poisson regression and an evaluation of the meaning and nature of overdispersion, followed by a comprehensive analysis of the negative binomial distribution and of its parameterizations into various models for evaluating count data.
- Electronic book text | 576 pages
- 31 Mar 2011
- CAMBRIDGE UNIVERSITY PRESS
- Cambridge University Press (Virtual Publishing)
- Cambridge, United Kingdom
- 2nd Revised edition
- 36 b/w illus. 170 tables
Table of contents
Preface; 1. Introduction; 2. The concept of risk; 3. Overview of count response models; 4. Methods of estimation and assessment; 5. Assessment of count models; 6. Poisson regression; 7. Overdispersion; 8. Negative binomial regression; 9. Negative binomial regression: modeling; 10. Alternative variance parameterizations; 11. Problems with zero counts; 12. Censored and truncated count models; 13. Handling endogeneity and latent class models; 14. Count panel models; 15. Bayesian negative binomial models; Appendix A. Constructing and interpreting interactions; Appendix B. Data sets and Stata files; References; Index.
'Students, developers, and practitioners in this area will all want to have this thorough guide close at hand. The wealth of theory and extensive applications using 'real' data sets and contemporary software will provide a crucial resource for their research.' William Greene, New York University 'This is a well-researched practically oriented book on an important class of models relevant to over-dispersed count data. Recommended.' John Nelder, Imperial College London 'Every model currently offered in commercial statistical software is discussed in detail ... well written and can serve as an excellent reference book for applied statisticians who would use negative binomial regression modelling for undergraduate students or graduate students.' Yuehua Wu, Zentralblatt MATH 'I would recommend this book to researchers and students who would like to gain an overview of the negative binomial distribution and its extensions.' Fiona McElduff, University College London 'The text is well-written, easy-to-read but once started, is difficult to put down as each chapter unfolds the intricacies of the distribution.' International Statistical Review 'The second edition of Negative Binomial Regression is a unique statistical textbook. It is a very enjoyable read! It not only provides statistical fundamentals, but also provides historical perspectives and expert insights. This book is an excellent introduction for someone new to modeling count data, as well as an invaluable resource for the experienced practitioner grappling with complex overdispersed data.' Elizabeth Kelly, Statistical Sciences Group, Los Alamos National Laboratory 'As with all of Joe Hilbe's books this text is thorough and scholarly with an extensive list of references. Important theorems and other theoretical results are presented but are presented to be informative rather than to develop and teach the theory.' Michael R. Chernick, Significance '... a valuable hands-on introduction to negative binomial regression and the analysis of count data in general. I am also pleased to see an advocation of the utility of the negative binomial distribution in applied work.' Psychometrika
About Joseph M. Hilbe
Joseph M. Hilbe is a Solar System Ambassador with NASA's Jet Propulsion Laboratory at the California Institute of Technology, an adjunct professor of statistics at Arizona State University, and an emeritus professor at the University of Hawaii. Professor Hilbe is an elected fellow of the American Statistical Association and an elected member of the International Statistical Institute (ISI), for which he is Chair of the ISI International Astrostatistics Network. He is the author of Logistic Regression Models (Chapman and Hall/CRC, 2009), a leading text on the subject, and co-author of R for Stata Users (Springer, 2010, with R. Muenchen), Generalized Estimating Equations (Chapman and Hall/CRC, 2002, with J. Hardin) and Generalized Linear Models and Extensions (Stata Press, 2001 and 2007, also with J. Hardin).