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 language | English (US) |
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Pages (from-to) | 83-104 |
Number of pages | 22 |
Journal | Psychological Methods |
Volume | 7 |
Issue number | 1 |
DOIs | |
State | Published - Mar 2002 |
ASJC Scopus subject areas
- Psychology (miscellaneous)