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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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James Jaccard
Choi K. Wan
Rob Turrisi
Multivariate Behavioral Research
University at Albany, State University of New York
Cancer Institute (WIA)
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Jaccard et al. (Mon,) studied this question.
www.synapsesocial.com/papers/69d9a2a50d540cafc583695a — DOI: https://doi.org/10.1207/s15327906mbr2504_4