On the Testing of complete causal mediation and its applications

TL;DR

This paper evaluates and improves the Complete Mediation Test (CMT) for causal mediation analysis, especially in Mendelian Randomization, by proposing a standardized criterion and assessing its performance through simulations.

Contribution

It introduces the standardized absolute proportion of mediation (SAPM) as a new criterion for CMT and systematically evaluates its effectiveness in MR studies.

Findings

SAPM offers the best performance among criteria tested

Proper thresholds depend on mediator and outcome types

SAPM strengthens evidence for complete mediation

Abstract

The Complete Mediation Test (CMT) serves as a specialized approach of mediation analysis to assess whether an independent variable A, influences an outcome variable Y exclusively through a mediator M, without any direct effect. An application of CMT lies in Mendelian Randomization (MR) studies, where it can be used to investigate non-pleiotropy, that is, to test whether genetic variants impact a disease outcome solely through their effect on a target exposure variable. Traditionally, CMT has relied on two significance-based criteria and a proportion-based criterion with a heuristic threshold that has not been rigorously evaluated. In this paper, we explored the theoretical properties of conventional CMT, and proposed using standardized absolute proportion of mediation (SAPM) as a criterion for CMT. We, systematically assess the performance of various CMT criteria via simulation, and demonstrate their practical utility in the context of MR studies. Our results indicate that the offers the best performance. We also propose using different optimal thresholds depending on whether the mediator and outcome are continuous or binary. The SAPM with proper thresholds ensures that the indirect pathway meaningfully accounts for the effect of the exposure on the outcome, thereby strengthening the case for complete mediation.