Full Versus Partial Mediation
A mediator variable can either account for all or some of the observed relationship between two variables.
Full mediation
Maximum evidence for mediation, also called full mediation, would occur if inclusion of the mediation variable drops the relationship between the independent variable and dependent variable (see pathway c in diagram above) to zero. This rarely, if ever, occurs. The most likely event is that c becomes a weaker, yet still significant path with the inclusion of the mediation effect.
Partial mediation
Partial mediation maintains that the mediating variable accounts for some, but not all, of the relationship between the independent variable and dependent variable. Partial mediation implies that there is not only a significant relationship between the mediator and the dependent variable, but also some direct relationship between the independent and dependent variable.
In order for either full or partial mediation to be established, the reduction in variance explained by the independent variable must be significant as determined by one of several tests, such as the Sobel test. The effect of an independent variable on the dependent variable can become nonsignificant when the mediator is introduced simply because a trivial amount of variance is explained (i.e., not true mediation). Thus, it is imperative to show a significant reduction in variance explained by the independent variable before asserting either full or partial mediation. It is possible to have statistically significant indirect effects in the absence of a total effect. This can be explained by the presence of several mediating paths that cancel each other out, and become noticeable when one of the cancelling mediators is controlled for. This implies that the terms 'partial' and 'full' mediation should always be interpreted relative to the set of variables that are present in the model. In all cases, the operation of "fixing a variable" must be distinguished from that of "controlling for a variable," which has been inappropriately used in the literature. The former stands for physically fixing, while the latter stands for conditioning on, adjusting for, or adding to the regression model. The two notions coincide only when all error terms (not shown in the diagram) are statistically uncorrelated. When errors are correlated, adjustments must be made to neutralize those correlations before embarking on mediation analysis (see Bayesian Networks).
Read more about this topic: Mediation (statistics)
Famous quotes containing the words full and/or partial:
“Only he who can view his own past as an abortion sprung from compulsion and need can use it to full advantage in the present. For what one has lived is at best comparable to a beautiful statue which has had all its limbs knocked off in transit, and now yields nothing but the precious block out of which the image of one’s future must be hewn.”
—Walter Benjamin (1892–1940)
“There is no luck in literary reputation. They who make up the final verdict upon every book are not the partial and noisy readers of the hour when it appears; but a court as of angels, a public not to be bribed, not to be entreated, and not to be overawed, decides upon every man’s title to fame. Only those books come down which deserve to last.”
—Ralph Waldo Emerson (1803–1882)