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  1. Home
  2. Books
  3. Negative Binomial Regression
  • Cited by 500
Publisher:
Cambridge University Press
Online publication date:
June 2012
Print publication year:
2007
Online ISBN:
9780511811852
DOI:
https://doi.org/10.1017/CBO9780511811852
Subjects:
Epidemiology Public Health and Medical Statistics, Medicine, Statistical Theory and Methods, Statistics and Probability
Information

Book description

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 before been 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 negative binomial 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.

Reviews

'I would recommend this book to researchers and students who would like to gain an overview of the negative binomial distribution and its extensions.'

Fiona McElduff - University College London

'The text is well-written, easy-to-read but once started, is difficult to put down as each chapter unfolds the intricacies of the distribution.'

Source: International Statistical Review

'Every model currently offered in commercial statistical software is discussed in detail…well written and can serve as an excellent reference book for applied statisticians who would use negative binomial regression modelling for undergraduate students or graduate students.'

Yuehua Wu Source: Zentralblatt MATH

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Contents

Contents
References
References
References
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