Modeling count data
著者
書誌事項
Modeling count data
Cambridge University Press, 2014
- : hardback
- : paperback
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
This entry-level text offers clear and concise guidelines on how to select, construct, interpret, and evaluate count data. Written for researchers with little or no background in advanced statistics, the book presents treatments of all major models using numerous tables, insets, and detailed modeling suggestions. It begins by demonstrating the fundamentals of modeling count data, including a thorough presentation of the Poisson model. It then works up to an analysis of the problem of overdispersion and of the negative binomial model, and finally to the many variations that can be made to the base count models. Examples in Stata, R, and SAS code enable readers to adapt models for their own purposes, making the text an ideal resource for researchers working in health, ecology, econometrics, transportation, and other fields.
目次
- Preface
- 1. Varieties of count data
- 2. Poisson regression
- 3. Testing overdispersion
- 4. Assessment of fit
- 5. Negative binomial regression
- 6. Poisson inverse Gaussian regression
- 7. Problems with zeros
- 8. Modeling under-dispersed count data - generalized Poisson
- 9. Complex data: more advanced models
- Appendix A: SAS code
- References
- Index.
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