title: The relative trustworthiness of inferential tests of the indirect effect in statistical mediation analysis: does method really matter?
abstract: A content analysis of 2 years of Psychological Science articles reveals inconsistencies in how researchers make inferences about indirect effects when conducting a statistical mediation analysis. In this study, we examined the frequency with which popularly used tests disagree, whether the method an investigator uses makes a difference in the conclusion he or she will reach, and whether there is a most trustworthy test that can be recommended to balance practical and performance considerations. We found that tests agree much more frequently than they disagree, but disagreements are more common when an indirect effect exists than when it does not. We recommend the bias-corrected bootstrap confidence interval as the most trustworthy test if power is of utmost concern, although it can be slightly liberal in some circumstances. Investigators concerned about Type I errors should choose the Monte Carlo confidence interval or the distribution-of-the-product approach, which rarely disagree. The percentile bootstrap confidence interval is a good compromise test.
authors: 1School of Communication, The Ohio State University.
authors: Andrew F
authors: AF
authors: Hayes
authors: Michael
authors: M
authors: Scharkow
mesh_terms: D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D006801:Humans; D009010:Monte Carlo Method; D013223:Statistics as Topic / Q000592:standards
keywords: Sobel test; bootstrapping; hypothesis testing; indirect effects; mediation analysis; statistical analyses