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Plots, Transformations, and Regression: An Introduction to Graphical Methods of Diagnostic Regression Analysis.
Abstract
This handbook provides a detailed, down-to-earth introduction to regression diagnostic analysis, a technique of growing importance for work in applied statistics. Heavily illustrated, with numerous examples to illuminate the discussion, this timely volume outlines methods for regression models, stressing detection of outliers and inadequate models; describes the transformation of variables in an equation, particularly the response; and considers such advanced topics as generalized linear models. A useful guide that combines lucid explanations with up-to-date research findings.
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Citations
Cited by
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Principles and procedures of exploratory data analysis.
Behrens, J. T. (1997) · Psychological Methods · doi:10.1037/1082-989x.2.2.131 · Cited by 465
Wu, W., Zhang, C., Lin, W., Chen, Q., Guo, X., Qian, Y., & Zhang, L. (2015) · PLOS ONE · doi:10.1371/journal.pone.0119575 · Cited by 47
Metadata
- Authors
- Hodges, J. S., & Atkinson, A. C.
- Venue
- Journal of the American Statistical Association
- Publisher
- JSTOR
- Published
- 1987-06
- Volume
- 82
- Issue
- 398
- Pages
- 689
- ISSN
- 0162-1459 (ISSN-L)
- OpenAlex
- W2096590196
- Cited by
- 396
- References
- 0
- FWCI
- 5.68
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Plots, Transformations, and Regression: An Introduction to Graphical Methods of Diagnostic Regression Analysis. https://app.cochat.ai/papers/10.2307/2289498
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- Hodges, J. S., & Atkinson, A. C. (1987). Plots, Transformations, and Regression: An Introduction to Graphical Methods of Diagnostic Regression Analysis. Journal of the American Statistical Association. https://doi.org/10.2307/2289498
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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.
