Testing the significance of mediating effects with WarpPLS using the Preacher & Hayes approach

This post refers to the use of WarpPLS to test a mediating effect using what is often referred to as the Preacher and Hayes approach. This approach employs the Sobel's standard error method (for a recent discussion, see: Kock, 2013). You can also test mediating effects directly with WarpPLS, using indirect and total effect outputs:

http://warppls.blogspot.com/2013/04/testing-mediating-effects-directly-with.html

Previously I also discussed on this blog the classic approach proposed by Baron & Kenny (1986) to test the significance of mediating effects with WarpPLS.

An approach that is an alternative to Baron & Kenny's (1986) approach has been proposed by Preacher & Hayes (2004) to test the significance of mediating effects. This approach has been further extended by Hayes & Preacher (2010) for nonlinear relationships.

These approaches are implemented through an Excel spreadsheet available from the “Resources” area of the WarpPLS.com site, under “Excel files”. The spreadsheet, which implements the Sobel's standard error method, can be used with coefficients generated based on linear and nonlinear analyses.

The Excel spreadsheet above takes as inputs coefficients generated by WarpPLS, including path coefficients and their standard errors. The formulas used in it are discussed in a recent publication (Kock, 2014). The outputs are Sobel’s standard errors, product path coefficients, as well as T and P values, for mediating effects.

References

Baron, R.M., & Kenny, D.A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality & Social Psychology, 51(6), 1173-1182.

Hayes, A.F., & Preacher, K.J. (2010). Quantifying and testing indirect effects in simple mediation models when the constituent paths are nonlinear. Multivariate Behavioral Research, 45(4), 627-660.

Kock, N. (2014). Advanced mediating effects tests, multi-group analyses, and measurement model assessments in PLS-based SEM. International Journal of e-Collaboration, 10(3), 1-13.
(http://www.scriptwarp.com/warppls/pubs/Kock_2014_UseSEsESsLoadsWeightsSEM.pdf)

Preacher, K.J., & Hayes, A.F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36 (4), 717-731.