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The Detection and Interpretation of Interaction Effects Between Continuous Variables in Multiple Regression
Abstract
issues in the detection and interpretation of interaction effects between quantitative variables in multiple regression analysis are discussed. Recent articles by Cronbach (1987) and Dunlap and Kemery (1987) suggested the use of two transformations to reduce "problems" of multicollinearity. These transformations are discussed in the context of the conditional nature of multiple regression with product terms. It is argued that although additive transformations do not affect the overall test of statistical interaction, they do affect the interpretational value of regression coefficients. Factors other than multicollinearity that may account for failures to observe interaction effects are noted.
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Cited by
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Gerber, M., & Pühse, U. (2009) · Scandinavian Journal of Public Health · doi:10.1177/1403494809350522 · Cited by 305
Schmitt, A., Den Hartog, D. N., & Belschak, F. D. (2016) · Journal of Occupational and Organizational Psychology · doi:10.1111/joop.12143 · Cited by 288
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Metadata
- Authors
- Jaccard, J., Wan, C. K., & Turrisi, R.
- Venue
- Multivariate Behavioral Research
- Publisher
- Informa UK Limited
- Published
- 1990-10
- Volume
- 25
- Issue
- 4
- Pages
- 467-478
- ISSN
- 0027-3171 (ISSN-L)
- 1532-7906
- OpenAlex
- W2087494123
- Cited by
- 743
- References
- 0
- FWCI
- 1.28
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: The Detection and Interpretation of Interaction Effects Between Continuous Variables in Multiple Regression. https://app.cochat.ai/papers/10.1207/s15327906mbr2504_4
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- Jaccard, J., Wan, C. K., & Turrisi, R. (1990). The Detection and Interpretation of Interaction Effects Between Continuous Variables in Multiple Regression. Multivariate Behavioral Research. https://doi.org/10.1207/s15327906mbr2504_4
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