A large number of approaches have been proposed for estimating and testing the significance of indirect effects in mediation models. In this study, four sets of Monte Carlo simulations involving full latent variable structural equation models were run in order to contrast the effectiveness of the currently popular bias-corrected bootstrapping approach with the simple test of joint significance approach. The results from these simulations demonstrate that the test of joint significance had more power than bias-corrected bootstrapping and also yielded more reasonable Type I errors.

Additional Metadata
Keywords bias-corrected bootstrapping, indirect effects, mediation, SEM, simulation
Persistent URL dx.doi.org/10.1177/0013164415593777
Journal Educational and Psychological Measurement
Citation
Leth-Steensen, C, & Gallitto, E. (Elena). (2016). Testing Mediation in Structural Equation Modeling: The Effectiveness of the Test of Joint Significance. Educational and Psychological Measurement, 76(2), 339–351. doi:10.1177/0013164415593777