The impact of measurement error and omitting confounders on statistical inference of mediation effects and tools for sensitivity analysis.

To make valid statistical inferences from mediation analysis, a number of assumptions need to be assessed. Among the assumptions, 2 frequently discussed ones are (a) the independent variable, mediator, and outcome variables are measured without error; and (b) no confounders of the effects in the mediation model are omitted. The impact of violating either assumption alone on statistical inference of mediation has been discussed in previous literature. In practice, violations of the 2 assumptions often co-occur. In this study, we analytically investigated the effects of measurement error and omitting confounders on statistical inference of mediation effects, including both point estimation and significance testing. Based on the analytical results, we proposed sensitivity analysis techniques for assessing the robustness of mediation inference to the violation of the 2 assumptions. To implement the techniques, we developed R functions and a user-friendly web tool. Simulated-data and real-data examples were provided for illustrations. We hope the developed tools will help researchers conduct sensitivity analyses of mediation inference more conveniently. (PsycInfo Database Record (c) 2021 APA, all rights reserved).