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Regression Analysis of Count Data
Abstract
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 a comprehensive account of models and methods to interpret such data. The authors have conducted research in the field for nearly fifteen years and in this work 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, 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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Citations
Cited by
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Estimating log models: to transform or not to transform?
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Detecting differential usage of exons from RNA-seq data
Anders, S., Reyes, A., & Huber, W. (2012) · Genome Research · doi:10.1101/gr.133744.111 · Cited by 1,545
Emotions and Information Diffusion in Social Media—Sentiment of Microblogs and Sharing Behavior
Stieglitz, S., & Dang-Xuan, L. (2013) · Journal of Management Information Systems · doi:10.2753/mis0742-1222290408 · Cited by 1,604
Metadata
- Authors
- Cameron, A. C., & Trivedi, P. K.
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 1998
- OpenAlex
- W4302853952
- Cited by
- 3,147
- References
- 0
- FWCI
- 8.41
- Type
- book
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.