The indirect effect is omitted variable bias. A cautionary note on the theoretical interpretation of products-of-coefficients in mediation analyses

Abstract

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’ when using observational data: 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 add to the existing warnings on mediation analyses and cultivate a more critical interpretation of ‘indirect effects’ in communication science.