Regression Analysis of Count Data
Regression Analysis of Count Data
Pravin K. Trivedi, Indiana University, Bloomington
Students in both social and natural sciences often seek regression methods to explain the frequency of events, such as visits to a doctor, auto accidents, or new patents awarded. This book, now in its second edition, 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 researchers and practitioners working with widely different types of data and software in areas such as applied statistics, econometrics, marketing, operations research, actuarial studies, demography, biostatistics and quantitative social sciences. The new material includes new theoretical topics, an updated and expanded treatment of cross-section models, coverage of bootstrap-based and simulation-based inference, expanded treatment of time series, multivariate and panel data, expanded treatment of endogenous regressors, coverage of quantile count regression, and a new chapter on Bayesian methods.
- Gives up-to-date and comprehensive coverage of different types of count data
- Provides a guide to implementation of models that is both systematic and amply illustrated with real empirical examples
- Supported by additional resources such as data, template programs and bibliographic materials valuable to instructors
Product details
July 2013Paperback
9781107667273
596 pages
226 × 152 × 33 mm
0.79kg
17 b/w illus. 56 tables
Available
Table of Contents
- 1. Introduction
- 2. Model specification and estimation
- 3. Basic count regression
- 4. Generalized count regression
- 5. Model evaluation and testing
- 6. Empirical illustrations
- 7. Time series data
- 8. Multivariate data
- 9. Longitudinal data
- 10. Endogenous regressors and selection
- 11. Flexible methods for counts
- 12. Bayesian methods for counts
- 13. Measurement errors.
