The Detection and Interpretation of Interaction Effects Between Continuous Variables in Multiple Regression

James Jaccard, Choi K. Wan, Robert Turrisi

Research output: Contribution to journalArticle

407 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)467-478
Number of pages12
JournalMultivariate Behavioral Research
Volume25
Issue number4
DOIs
StatePublished - Oct 1 1990

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Experimental and Cognitive Psychology
  • Arts and Humanities (miscellaneous)

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