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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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).
" ...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
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