Cart

Unlocking potential with the best learning and research solutions

Look Inside Negative Binomial Regression

Negative Binomial Regression

2nd Edition

$106.00 (C)

Author: Joseph M. Hilbe, Jet Propulsion Laboratory, California Institute of Technology; and Arizona State University

Date Published: April 2011
availability: Available
format: Hardback
isbn: 9780521198158

Rate & review

$ 106.00 (C)
Hardback

Add to cart Add to wishlist

Other available formats:
eBook

Looking for an examination copy?

This title is not currently available for examination. However, if you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact collegesales@cambridge.org providing details of the course you are teaching.

Description

Contents

Resources

Courses

About the Authors

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.
- Fully revised to incorporate recent software developments
- Every model currently offered in a commercial statistical software package is discussed in detail
- Data sets and additional code available on a companion website
Read more
Reviews & endorsements
"As with all of Joe Hilbe's books this text is thorough and scholarly with an extensive list of references. The text is well-written and for the most part easy to understand."
Michael R. Chernick, Significance
"For any applied statistician who needs negative binomial models in their research and applications, it is usually not easy to find a book to provide both theoretical fundamentals and practical expert insights. This books meets such a need perfectly. Overall, this is a very well-written book. Its statistical rigor and expert insights in negative binomial modeling should be very appealing to readers of Technometrics."
Xianggui Qu, Oakland University for Technometrics
See more reviews
Customer reviews

Not yet reviewed
Be the first to review

Log in to review

Review was not posted due to profanity
×

, create a review

(If you're not , sign out)

Please enter the right captcha value

Please enter a star rating.

Your review must be a minimum of 12 words.

How do you rate this item?

Reviews must contain at least 12 words about the product.

×

Product details
- Edition: 2nd Edition
- Date Published: April 2011
- format: Hardback
- isbn: 9780521198158
- length: 572 pages
- dimensions: 231 x 155 x 36 mm
- weight: 1.13kg
- contains: 36 b/w illus. 170 tables
- availability: Available
Table of Contents
Preface
1. Introduction
2. The concept of risk
3. Overview of count response models
4. Methods of estimation and assessment
5. Assessment of count models
6. Poisson regression
7. Overdispersion
8. Negative binomial regression
9. Negative binomial regression: modeling
10. Alternative variance parameterizations
11. Problems with zero counts
12. Censored and truncated count models
13. Handling endogeneity and latent class models
14. Count panel models
15. Bayesian negative binomial models
Appendix A. Constructing and interpreting interactions
Appendix B. Data sets and Stata files
References
Index.
Look Inside

General Resources

Find resources associated with this title

Back to resources home

Type	Name	Unlocked *	Format	Size

Showing of

This title is supported by one or more locked resources. Access to locked resources is granted exclusively by Cambridge University Press to instructors whose faculty status has been verified. To gain access to locked resources, instructors should sign in to or register for a Cambridge user account.

Please use locked resources responsibly and exercise your professional discretion when choosing how you share these materials with your students. Other instructors may wish to use locked resources for assessment purposes and their usefulness is undermined when the source files (for example, solution manuals or test banks) are shared online or via social networks.

Supplementary resources are subject to copyright. Instructors are permitted to view, print or download these resources for use in their teaching, but may not change them or use them for commercial gain.

If you are having problems accessing these resources please contact lecturers@cambridge.org.

Instructors have used or reviewed this title for the following courses
- Applied Data Analysis
- Psychological Statistics ll
- Statistics for Demographic Data 2
Author
Joseph M. Hilbe, Jet Propulsion Laboratory, California Institute of Technology; and Arizona State University
Joseph M. Hilbe is a Solar System Ambassador with NASA's Jet Propulsion Laboratory at the California Institute of Technology, an adjunct professor of statistics at Arizona State University, and an emeritus professor at the University of Hawaii. Professor Hilbe is an elected fellow of the American Statistical Association and an elected member of the International Statistical Institute (ISI), for which he is Chair of the ISI International Astrostatistics Network. He is the author of Logistic Regression Models (Chapman and Hall/CRC, 2009), a leading text on the subject, and co-author of R for Stata Users (Springer, 2010, with R. Muenchen), Generalized Estimating Equations (Chapman and Hall/CRC, 2002, with J. Hardin) and Generalized Linear Models and Extensions (Stata Press, 2001 and 2007, also with J. Hardin).