Abstract:
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An important problem within the social, behavioral, and health sciences is to partition an exposure effect among specific pathway effects and to quantify the importance of each pathway. Mediation analysis based on the potential outcomes framework is an important tool when addressing this problem. In this project, we consider the estimation of mediation effects for the proportional hazards model in a survival context. We give a precise definition of the total effect, natural indirect effect, and natural direct effect on the hazard function scale within the standard two-stage mediation framework. To estimate the mediation effects, we propose a mediation formula approach in which simple parametric models (fractional polynomials or restricted cubic splines) are utilized to approximate the baseline log cumulative hazard function. Simulation study results demonstrate low bias of mediation effect estimators and close-to-nominal coverage probability of confidence intervals for a wide range of complex hazard shapes. We apply this new method to data from the Jackson Heart Study to estimate the mediation effect of blood pressure on the relationship between smoking and incident stroke events.
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