Modeling Count Data

In association with, we are proud to offer Modeling Count Data published by the Cambridge University Press. This entry-level guide offers readers an in-depth look at how data is selected, constructed, and evaluated.

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Modeling Count Data

Modeling Count Data

Written by author Joseph M. Hilbe, this book is for statistic researchers of all kinds. There are multiple tables, models, and graphs that demonstrate how they are collected, and true to its “modeling” nature, this book explains it all.

At the beginning of the book, you will understand the basic fundamentals of linear regression. Then, readers will “work [their] way up” to the analysis of the Poisson and negative binomial models and overdispersion. Stata, R, and SAS code examples are provided.

According to William Green, at NYU:

“The negative binomial model is the foundation for modern analysis of count data. Joe Hilbe’s work collects a vast wealth of technical and practical information for the analyst. The theoretical developments and thoroughly worked applications use realistic data sets and a variety of computer packages. They will provide to the practitioner an indispensable guide for basic single-equation count data regressions and advanced applications with recently developed model extensions and methods.” 

The book is available both in print and in paperback editions.

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Modeling Count Data is not affiliated with the Cambridge University Press.