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.
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" ...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
"...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
Book Description
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.
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30 of 30 people found the following review helpful:
5.0 out of 5 stars
important topics,
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This review is from: Regression Analysis of Count Data (Econometric Society Monographs) (Paperback)
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:
4.0 out of 5 stars
It is true!,
By Alex (Greece) - See all my reviews
This review is from: Regression Analysis of Count Data (Econometric Society Monographs) (Paperback)
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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Inside This Book
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First Sentence:
This book is concerned with models of event counts. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
exponential conditional mean function, exponential mean function, overdispersion tests, count data regression models, count regression models, recreational boating trips, hurdle model, count data analysis, maximum likelihood output, major derogatory reports, specified conditional mean, baseline density, count data models, recording probability, nonnested models, quadratic variance function, maximum likelihood standard errors, information matrix equality, binary poisson, apparent contagion, conditional moment tests, asymptotically equivalent version, omitted regressors, count models, true contagion Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, United States, Lake Somerville, Two Crossings Theorem New!
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
This book is concerned with models of event counts. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
exponential conditional mean function, exponential mean function, overdispersion tests, count data regression models, count regression models, recreational boating trips, hurdle model, count data analysis, maximum likelihood output, major derogatory reports, specified conditional mean, baseline density, count data models, recording probability, nonnested models, quadratic variance function, maximum likelihood standard errors, information matrix equality, binary poisson, apparent contagion, conditional moment tests, asymptotically equivalent version, omitted regressors, count models, true contagion Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, United States, Lake Somerville, Two Crossings Theorem New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 49
books:
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31
books
cite this book:
See all 31 books citing this book
- Markov Chain Monte Carlo in Practice (Chapman & Hall/CRC Interdisciplinary Statistics) by W.R. Gilks in Back Matter (1), and Back Matter (2)
- Working Papers by Peter G Peterson Institute for International Economics in Back Matter (1), and Back Matter (2)
- Random Counts - VLM. 1 (Random Counts in Models & Structures) (v. 1) by G. P. Patil in Back Matter (1), and Back Matter (2)
- Time Series (International Library of Critical Writings in Econometrics) by Andrew C. Harvey in Back Matter (1), and Back Matter (2)
- Semiparametric Regression (Cambridge Series in Statistical and Probabilistic Mathematics) by David Ruppert in Back Matter (1), and Back Matter (2)
See all 49 books this book cites
- Fertility, Family Planning and Population Policy in China (Routledge Studies in Asia's Transformations) by Chiung-Fang Chang on page 77, and page 142
- Nationalist Mobilization and the Collapse of the Soviet State (Cambridge Studies in Comparative Politics) by Mark R. Beissinger on page 131, and page 239
- Bayesian Models for Categorical Data (Wiley Series in Probability and Statistics) by Professor Peter Congdon on page 193, and page 317
- A Guide to Modern Econometrics by Marno Verbeek in Back Matter (1), and Back Matter (2)
- Econometric Analysis of Health Data by Andrew M. Jones on page 116, and page 132
See all 31 books citing this book
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