Negative binomial regression

Bibliographic Information

Negative binomial regression

Joseph M. Hilbe

Cambridge University Press, 2012

2nd ed., repr. with corrections

  • : hardback

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Note

Includes bibliographical references (p. 532-540) and index

Description based on: 8th printing 2014

Description and Table of Contents

Description

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.

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.

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