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Negative Binomial Regression, Second Edition

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Joseph M. Hilbe
Publisher: Cambridge University Press
Copyright: 2011
ISBN-13: 978-0-521-19815-8
Pages: 553; hardcover
Price: $78.50
Joseph M. Hilbe
Publisher: Cambridge University Press
Copyright: 2011
Pages: 553; eBook
Price: $0.00
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Comment from the Stata technical group

Negative Binomial Regression, Second Edition, by Joseph M. Hilbe, reviews the negative binomial model and its variations. Negative binomial regression—a recently popular alternative to Poisson regression—is used to account for overdispersion, which is often encountered in many real-world applications with count responses.

Negative Binomial Regression covers the count response models, their estimation methods, and the algorithms used to fit these models. Hilbe details the problem of overdispersion and ways to handle it. The book emphasizes the application of negative binomial models to various research problems involving overdispersed count data. Much of the book is devoted to discussing model-selection techniques, the interpretation of results, regression diagnostics, and methods of assessing goodness of fit.

Hilbe uses Stata extensively throughout the book to display examples. He describes various extensions of the negative binomial model—those that handle excess zeros, censored and truncated data, panel and longitudinal data, and data from sample selection.

Negative Binomial Regression is aimed at those statisticians, econometricians, and practicing researchers analyzing count-response data. The book is written for a reader with a general background in maximum likelihood estimation and generalized linear models, but Hilbe includes enough mathematical details to satisfy the more theoretically minded reader.

This second edition includes added material on finite-mixture models; quantile-count models; bivariate negative binomial models; and various methods of handling endogeneity, including the generalized method of moments.

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