At last - a book devoted to the negative binomial model and its many variations. Every model currently offered in commercial statistical software packages is discussed in detail - how each is derived, how each resolves a distributional problem, and numerous examples of their application. Many have never beforebeen thoroughly examined in a text on count response models: the canonical negative binomial; the NB-P model, where the negative binomial exponent is itself parameterized; and negative binomial mixed models. As the models address violations of the distributional assumptions of the basic Poisson model, identifying and handling overdispersion is a unifying theme. For practising researchers and statisticians who need to update their knowledge of Poisson and negativebinomial models, the book provides a comprehensive overview of estimating methods and algorithms used to model counts, as well as specific guidelines on modeling strategy and how each model can be analyzed to access goodness-of-fit. INDICE: Preface; Introduction; 1. Overview of count response models; 2. Methods of estimation; 3. The Poisson model; 4. Overdispersion; 5. Negative binomial regression: basics; 6. Negative binomial regression: modeling; 7. Alternative variance parameterizations; 8. Problems with zero counts; 9. Negative binomial with censoring, truncation, and sample selection; 10. Negative binomial panel models; Appendix A: Negative binomial log-likelihood functions; AppendixB: Deviance functions; Appendix C: ML negative binomial Code; Appendix D: Negative binomial variance functions; Appendix E: Data sets; References; Author index; Index.
- ISBN: 978-0-521-85772-7
- Editorial: Cambridge University Press
- Encuadernacion: Cartoné
- Páginas: 251
- Fecha Publicación: 31/12/2008
- Nº Volúmenes: 1
- Idioma: Inglés