Negative binomial regression / Joseph M. Hilbe.
Material type:
TextPublication details: Cambridge, UK ; New York : Cambridge University Press, 2011.Edition: 2nd edDescription: 553 p. : illISBN: - 9780521198158
- 0521198151
- QA161 H641 N 2011
English Books
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English Books
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MATRIX Library General Eng/FL.3 | General Books | QA161 H641 N 2011 (Browse shelf(Opens below)) | C.1 | Available | 1000385040 |
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| QA154.2 L36 Algebra / | QA154.2 S951 C3 1996 College Algebra Enhanced with Gaphing Utilities / | QA159 A652 1996 Approaches to algebra : | perspectives for research and teaching / | QA161 H641 N 2011 Negative binomial regression / | QA161 S693 N 2005 The numerical solution of systems of polynomials arising in engineering and science / | QA164 C771 I 2012 In pursuit of the traveling salesman : | mathematics at the limits of computation / | QA164 S425 H 2011 How to count : | an introduction to combinatorics / |
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.
HKBU library
YT2025 M08
"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 code are provided throughout the text, with additional code (plus SAS), derivations, and data provided on the book's website. Written for the practicing 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"--
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