Mediator variable

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A mediator variable (or mediating variable) in statistics is a variable that describes how rather than when effects will occur by accounting for the relationship between the independent and dependent variables. A mediating relationship is one in which the path relating A to C is mediated by a third variable (B).

For example, a mediating variable explains the actual relationship between the following variables. Most people will agree that older drivers (up to a certain point), are better drivers. Thus:

aging $\to$ better driving

But what is missing from this relationship is a mediating variable that is actually causing the improvement in driving: wisdom. The mediated relationship would look like the following:

aging $\to$ increased wisdom $\to$ better driving

(And yes, it could also be argued that instead of increased wisdom it is increased responsibility for one's actions, but separating those two is difficult to do.)

Mediating variables are often contrasted with moderating variables, which pinpoint the conditions under which an independent variable exerts its effects on a dependent variable. A moderating relationship can be thought of as an interaction. It occurs when the relationship between variables A and B depends on the level of C.

In fact, the best explanation of the above relationship is a combination of mediating and moderating variables. Increased age does often lead to increased wisdom, but it also requires the maintenance of good reflexes. Thus, there is an interaction between age and reflexes that serves as a moderating variable. Increasing age only improves driving until reflexes begin to suffer, at which point the moderator variable (age x reflexes) results in worse driving. Or:

aging $\to$ increased wisdom $\to$ better driving $\to$ worse driving
(until) aging $\to$ decline in reflexes $\nearrow$

In psychology factors are commonly seen as independent variables and outcomes as the dependent variables, and the effect of one upon the other is often mediated by processes.