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Regression Analysis of Count Data (Econometric Society Monographs), by A. Colin Cameron, Pravin K. Trivedi
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Students in both the natural and social sciences often seek regression models to explain the frequency of events, such as visits to a doctor, auto accidents or job hiring. This analysis provides the most comprehensive and up-to-date account of models and methods to interpret such data. The authors combine theory and practice to make sophisticated methods of analysis accessible to practitioners working with widely different types of data and software. The treatment will be useful to researchers in areas such as applied statistics, econometrics, operations research, actuarial studies, demography, biostatistics, and quantitatively-oriented sociology and political science. The book may be used as a reference work on count models or by students seeking an authoritative overview. The analysis is complemented by template programs available on the Internet through the authors' homepages.
- Sales Rank: #1810444 in Books
- Brand: Brand: Cambridge University Press
- Published on: 1998-09-28
- Original language: English
- Number of items: 1
- Dimensions: 8.98" h x .91" w x 5.98" l, 1.40 pounds
- Binding: Paperback
- 436 pages
- Used Book in Good Condition
Review
" ...an impressive piece of work in all respects: it provides the first comprehensive description of the subject, it is mathematically rigorous and easy to read, and it contains useful discussions, interesting applications, various exercises, and a precise presentation of a very large bibliography. This book will become a basic reference for students and researchers." Alain Monfort
"...collects an extensive amount of material which has not been treated before in a textbook. The text is well written and the examples...are very illustrative. Although the book appears in the series of econometric monographs it should also be studied by people from other fields of applied statistics." Mathematical Reviews
About the Author
A. Colin Cameron is Professor of Economics at the University of California, Davis. His research and teaching interests span a range of topics in microeconometrics. He is a past director of the Center on Quantitative Social Science at the University of California, Davis and is currently an associate editor of the Stata Journal. He is coauthor (with Pravin K. Trivedi) of the first edition of Regression Analysis of Count Data (Cambridge, 1998) and of Microeconometrics: Methods and Applications (Cambridge, 2005).
Pravin K. Trivedi is Distinguished Professor and J. H. Rudy Professor of Economics at Indiana University, Bloomington. His research and teaching interests are in microeconometrics and health economics. He served as co-editor of the Econometrics Journal from 2000 to 2007 and has been on the board of Journal of Applied Econometrics since 1988. He is coauthor (with A. Colin Cameron) of the first edition of Regression Analysis of Count Data (Cambridge, 1998) and of Microeconometrics: Methods and Applications (Cambridge, 2005).
Most helpful customer reviews
34 of 34 people found the following review helpful.
important topics
By Michael R. Chernick
This is a very thorough and authoritative treatment of regression methods for analyzing count data. It is very current and covers many topics not commonly found in books on point processes. Economic applications are emphasized but the broader applicability of the methods is eluded to.
The authors intent is for this book to be read by researchers, graduate students and practitioners in the many fields that make use of count data. Chapter 1 introduces count data, the Poisson distribution and the Poisson process and also shows how the Poisson process can be derived based on the assumption of independent and identically distributed exponential waiting times. It concludes with specification of regression models for counts and a number of practical examples where modeling count data would naturally arise. The importance of the integers is emphasized with the quote from Kronecker at the beginning of the chapter, "God made the integers, all the rest is the work of man."
Chapter 2 provides an extensive treatment of model specification and estimation methods. The authors cover many approaches and provide excellent references to the literature. Generalized linear models provide one common approach in the statistics literature and these methods are well described in this chapter.
Poisson regression is the main topic of Chapter 3 but the chapter goes on to discuss negative binomial models that handle overdispersion. An example of data on doctor's visits is used to illustrate the techniques. Statistical tests for overdispersion are also presented. A variety of other modeling techniques are also provided.
More general models including mixture models are considered in Chapter 4. Chapter 5 looks at ways of evaluating potential models. Chapter 6 provides some real economic data from health services to illustrate the methods of the earlier chapters.
Chapter 7 covers time series analysis for integer data. The authors provide information and literature that is not standard in a text on time series analysis but is applicable to count data.
Subsequent chapters deal with more complexity including multivariate data,longitudinal data analysis and measurement error models. Important recent developments in bootstrap methods and Bayesian statistics are covered in the context of problems for which these methods have demonstrated their value.
This is a great reference book for statisticians and econometricians interested in problems involving counting processes. It could also be used for a graduate school text on point process regression.
2 of 24 people found the following review helpful.
It is true!
By Alex
Well most prople are used in telling stories about the unapliability of economics in real life. That math and logic can not apply to most economic books! Most of the people say that economics are only theory.I will tell you that this book is one of a kind, reading it you will be able to have a better understanding of Econometrics.If you have enough money to pay the rent and some left buy this book ! its better than food!
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