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Regression Analysis: Theory, Methods, and Applications
Abstract
An up-to-date, rigorous, and lucid treatment of the theory, methods, and applications of regression analysis, and thus ideally suited for those interested in the theory as well as those whose interests lie primarily with applications. It is further enhanced through real-life examples drawn from many disciplines, showing the difficulties typically encountered in the practice of regression analysis. Consequently, this book provides a sound foundation in the theory of this important subject.
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Citations
Cited by
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Romero, R., Nien, J. K., Espinoza, J., Todem, D., Fu, W., Chung, H., Kusanovic, J. P., Gotsch, F., Erez, O., Mazaki-Tovi, S., et al. (2008) · The Journal of Maternal-Fetal & Neonatal Medicine · doi:10.1080/14767050701830480 · Cited by 675
The Intrinsic Estimator for Age‐Period‐Cohort Analysis: What It Is and How to Use It
Yang, Y., Schulhofer‐Wohl, S., Fu, W. J., & Land, K. C. (2008) · American Journal of Sociology · doi:10.1086/587154 · Cited by 503
Yang, Y., Fu, W. J., & Land, K. C. (2004) · Sociological Methodology · doi:10.1111/j.0081-1750.2004.00148.x · Cited by 440
McDowell, M. A., Dillon, C. F., Osterloh, J., Bolger, P. M., Pellizzari, E., Fernando, R., de Oca, R. M., Schober, S. E., Sinks, T., Jones, R. L., et al. (2004) · Environmental Health Perspectives · doi:10.1289/ehp.7046 · Cited by 364
Metadata
- Authors
- Chiu, S.-T., Sen, A., & Srivastava, M.
- Venue
- Technometrics
- Publisher
- JSTOR
- Published
- 1991-11
- Volume
- 33
- Issue
- 4
- Pages
- 479
- ISSN
- 0040-1706 (ISSN-L)
- OpenAlex
- W2797431976
- Cited by
- 594
- References
- 0
- FWCI
- 5.34
- Type
- journal article
- Language
- en
- Open access
- closed
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- Chiu, S.-T., Sen, A., & Srivastava, M. (1991). Regression Analysis: Theory, Methods, and Applications. Technometrics. https://doi.org/10.2307/1269427
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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.
