This paper intends to remind communication scientists that the indirect effect as estimated in mediation analyses is a statistical synonym for omitted variable bias (i.e., confounding or suppression). This simple fact questions the interpretability of statistically significant ‘indirect effects’ in observational designs: in social reality all variables correlate with each other to some extent - the so-called ‘crud factor’ - which means that omitted variable bias and ‘indirect effects’ at the population level are virtually guaranteed regardless of the actual variables involved in the statistical mediation model. As a result, there can be no inferential link between the observation of a significant indirect effect and a theoretical claim of mediation. Through this argument the paper hopes to cultivate a more critical attitude toward the interpretation of ‘indirect effects’ in observational communication science.
Unwarranted inferences from statistical mediation tests – An analysis of articles published in 2015
