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.
A substantial enhancement of the only text devoted entirely to the negative binomial model and its many variations.
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).
'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
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