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Negative binomial regression

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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.

Title Negative binomial regression / Joseph M. Hilbe. [electronic resource]
Edition Second edition.
Publisher Cambridge : Cambridge University Press
Creation Date 2011
Notes Title from publisher's bibliographic system (viewed on 05 Oct 2015).
Includes bibliographical references and index.
English
Content The concept of risk -- Overview of count response models -- Methods of estimation -- Assessment of count models -- Poisson regression -- Overdispersion -- Negative binomial regression -- Negative binomial regression: modeling -- Alternative variance parameterizations -- Problems with zero counts -- Censored and truncated count models -- Handling endogeneity and latent class models -- Count panel models -- Bayesian negative binomial models -- Appendix A. Constructing and interpreting interactions terms -- Appendix B. Data sets, commands, functions.
Extent 1 online resource (xviii, 553 pages) : digital, PDF file(s).
Language English
National Library system number 997010712507805171
MARC RECORDS
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