A common belief in the organizational sciences is that estimated interaction effects in ordinary least squares regression cannot be artifacts of common method variance (CMV). This belief rests on the claim that CMV universally attenuates estimated interaction effects. As a result, researchers frequently dismiss CMV concerns when testing moderated relationships. We present an analytic closed-form regression model demonstrating that this universal attenuation claim is false in commonplace scenarios. In particular, when a quadratic term legitimately affects the dependent variable (DV) in the presence of CMV, an estimated interaction effect may be purely artifactual. The common belief holds only in two special cases: (1) when quadratic terms have zero effect on the DV, or (2) when one primary term that enters the interaction is unambiguously unaffected by CMV. We conclude that researchers should apply all standard CMV precautions when testing moderated hypotheses; the fact that one is assessing interactions should not be viewed as a “get out of CMV jail free” card. In addition, we recommend estimating and reporting model specifications both with and without quadratic terms to assess robustness.
