Mediation refers to a statistical difference between a regression testing a direct path regressing treatment on outcome (c) and the indirect path (treatment on outcome accounting for the mediator or c′). The significance of the cross-product of the a path (treatment on the mediator) and b path (relation of the mediator to outcome, controlling for treatment) is widely viewed as one of the best tests of mediation (MacKinnon, Lockwood, Hoffman, West, & Sheeis, 2002). However, because the cross-product is generally not normally distributed (Preacher & Hayes, 2004), a nonparametric method using bootstrapping was applied (Preacher & Hayes, 2004, 2008). The present set of analyses based parameter estimates on 3,000 bootstrapped data sets. Values generated by normal theory and the bootstrapped cross-product values with bias-corrected and accelerated confidence intervals are shown in Table 3.
