Mediation Analysis

Statistical Analysis

A mediational hypothesis tests whether a third variable mediates (or accounts for) the relationship between an independent and dependent variable. Researchers refer to this third variable as a mediating variable. The mediating variable aims to fully mediate the relationship so that, when added to a model, it eliminates the independent variable’s effect on the dependent variable.

Researchers Baron and Kenny list out a series of four required steps to follow when running a mediational hypothesis. The researcher first determines whether the initial variable correlates with the outcome variable. This is important because it establishes that there is an effect for a third variable to mediate. Similarly, steps two and three are related to determine that there is a correlation between the initial variable and the mediator variable and between the outcome variable and the mediator variable. Finally, the last step is to establish the complete mediation across the variables. This means that adding the mediation variable will reduce the initial variable’s effect on the outcome variable to zero.

If the data satisfies all four of these steps, then according to the researchers, the data is reliable for a mediational hypothesis to work. It is important to note, however, that the completion of these steps does not mean that mediation has occurred, only that a mediation is one plausible model that would fit the data.

Related Pages: