A comparison of methods to test mediation and other intervening variable effects

David P. MacKinnon, Chondra M. Lockwood, Jeanne M. Hoffman, Stephen G. West, Virgil Sheets

Research output: Contribution to journalArticlepeer-review

5966 Scopus citations

Abstract

A Monte Carlo study compared 14 methods to test the statistical significance of the intervening variable effect. An intervening variable (mediator) transmits the effect of an independent variable to a dependent variable. The commonly used R. M. Baron and D. A. Kenny (1986) approach has low statistical power. Two methods based on the distribution of the product and 2 difference-in-coefficients methods have the most accurate Type I error rates and greatest statistical power except in 1 important case in which Type I error rates are too high. The best balance of Type I error and statistical power across all cases is the test of the joint significance of the two effects comprising the intervening variable effect.

Original languageEnglish (US)
Pages (from-to)83-104
Number of pages22
JournalPsychological Methods
Volume7
Issue number1
DOIs
StatePublished - Mar 2002

ASJC Scopus subject areas

  • Psychology (miscellaneous)

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