Evaluating and rejecting true mediation models: a cautionary note.

This research note describes an overlooked problem in understanding whether a given variable in a model truly acts as a mediator between some exogenous variable(s) and some final dependent factor. Demonstrations of mediation and the rules for identifying have relied on simple 3-variable models with an explicit direct effects alternative model as the competing explanation. Incorporating a 4th variable demonstrates that it is quite simple to reject mediation when a true form of mediation exists. In the presence of an unobserved relation, correlated error, between mediator variable and outcome variable, the 3-variable model will consistently show direct effects when, in fact, there is no direct effect of the exogenous variable. Applying well-established rules to test for mediation in this circumstance cannot distinguish a model in which pure mediation is rejected from a model in which true mediation is correct. This poses a fundamental problem for the typical assessment of mediation offered by the Baron and Kenny procedures.