| Literature DB >> 11928892 |
David P MacKinnon1, Chondra M Lockwood, Jeanne M Hoffman, Stephen G West, Virgil Sheets.
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.Mesh：
Year: 2002 PMID： 11928892 PMCID： PMC2819363 DOI： 10.1037/1082-989x.7.1.83
Source DB: PubMed Journal: Psychol Methods ISSN： 1082-989X