Objectives: A mediator is a psychosocial construct that is targeted by an intervention to bring about behavior change. Recent literature suggests that a widely used approach for assessing mediation, namely the causal steps method, can be severely statistically underpowered. This article describes three standard methods for assessing mediation: causal steps, difference in coefficients, and product of coefficients. We also demonstrate the use of asymmetric confidence limits (ACLs) in testing mediation.
Methods: We compared the results obtained by ACL construction with results obtained based on the causal steps and product of coefficients approaches to analyze data from the Seropositive Urban Men's Intervention Trial.
Results: ACL construction uncovered previously unidentified mediating factors. We also identified a marginally significant suppressor, which means that, with regard to this factor, the intervention had effects that were opposite from the desired direction.
Conclusions: ACLs are preferred for this type of analysis because of their statistical power and because they are informative regardless of whether the intervention has a significant effect on the outcome. Furthermore, ACLs present the size of the mediating effect rather than just a binary decision regarding significance.