Mediation FAQ:
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the RIPL Mediation Page Q. What articles would you suggest for someone just learning about mediation? A. Some good background references include:
Q. How do I conduct a mediation analysis? A. Mediation analysis
uses the estimates and standard errors from the following regression equations (MacKinnon,
1994):
If the effect of X on Y is zero when the mediator is included (c' = 0), there is evidence for mediation (Judd & Kenny, 1981a, 1981b). This would be full mediation. If the effect of X on Y is reduced when the mediator is included (c' < c), then the direct effect is said to be partially mediated. Q. How do you test for the significance of mediated effects? A. To calculate the significance of the mediated effect, divide the mediated effect by its' standard error (MacKinnon & Dwyer, 1993). The regression coefficients (a, b, c, and c' from above) and the standard errors for each of those regression coefficients (se_{c}, se_{a}, se_{b}, and se_{c'} ) come from the output from running the regressions above. Divide the mediated effect (a*b) by its' standard error. The result is a z-score.
The formula for this standard error (se_{ab})
of the mediated effect (a*b) is below (Sobel 1982, 1986). Details may be found in: Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. In S. Leinhardt (Ed.), Sociological Methodology 1982 (pp. 290-312). Washington, DC: American Sociological Association. Sobel, M. E. (1986). Some new results on indirect effects and their standard errors in covariance structure models. In N. Tuma (Ed.), Sociological Methodology 1986 (pp. 159-186). Washington, DC: American Sociological Association. Note that there is evidence that z_{ab }is not normally distributed.
There are also alternative methods to test the significane of the mediated effect. Q. What are the different components of mediation models? I've heard mediated effect, direct effect, etc. A. Using the regression coefficients from the models above, the components of a mediation model are Total effect = a*b + c' The total effect is the sum of direct and indirect effects of the X on the outcome (Y). Direct effect = c' The direct effect of X on Y when taking the mediator into account. Mediated effect = a*b The mediated effect is also called the indirect effect. This is because it is the part of the model that indirectly affects the outcome through the mediator. Q. What is the difference between an interaction effect and a mediation effect? A. Mediation implies a causal sequence among three variables X to M to Y (independent variable causes the mediator and the mediator causes the dependent variable). For example, an intervention may change social norms and this change in social norms prevented smoking. An interaction means that the effect of X on Y depends on the level of a third variable. No causal sequence is implied by interaction. For example, an intervention may be successful for males but not for females--an interaction effect. Q. What is the difference between a moderator effect and a mediation effect? A. A moderator effect is another term for an interaction effect. See above for the distinction between interaction effects and mediation effects. Q. Can you test for mediation in latent variable models? A. To test mediation in latent variable models, follow the same steps described above, substituting structural coefficients for regression coefficients. Q. What are good references for causal interpretation in mediation analysis? A. Some good references
for issues of causality and mediation are:
Q. Why doesn't c-c' equal a*b? A. See correspondence
with Julie Maloy.
A. See correspondence
with Julie Maloy.
A. See correspondence with Julie Maloy. |
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last modified: January 10, 2003 |