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

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          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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          Most cited references 15

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          The moderator-mediator variable distinction in social psychology research: Conceptual, strategic, and statistical considerations

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            The Decomposition of Effects in Path Analysis

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              Mediators, moderators, and tests for mediation.

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                Author and article information

                Journal
                Psychological Methods
                Psychological Methods
                American Psychological Association (APA)
                1939-1463
                1082-989X
                2002
                2002
                : 7
                : 1
                : 83-104
                Article
                2819363
                11928892
                © 2002

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