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Comparative Study
. 2002 Mar;7(1):83-104.
doi: 10.1037/1082-989x.7.1.83.

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

David P MacKinnon  1 , Chondra M Lockwood, Jeanne M Hoffman, Stephen G West, Virgil Sheets
Affiliations
Comparative Study

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

David P MacKinnon et al. Psychol Methods. 2002 Mar.

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.

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Figures

Figure 1
Figure 1
Path diagram and equations for the intervening variable model.
See this image and copyright information in PMC

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