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Activity Number: 56 - Causal Inference
Type: Contributed
Date/Time: Sunday, August 8, 2021 : 3:30 PM to 5:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #318629
Title: Testing for Joint Mediation Effects of Multiple Mediators
Author(s): Wei Hao* and Peter X.K. Song
Companies: University of Michigan and University of Michigan
Keywords: Constrained maximum likelihood; Lagrange multiplier; multi-dimensional mediators; structural equation model

Mediation analysis via structural equation models has become a widely used tool to study whether the effect of an exposure on an outcome is mediated by some intermediate factors. When multiple mediators are present, statistical inference on the joint mediation effect is challenging due to the involvement of composite null hypotheses with a large number of parameter configurations. We propose a simultaneous likelihood ratio test in which a block coordinate descent algorithm is invoked to solve the constrained likelihood under the irregular null parameter space using the Lagrange Multiplier approach. We establish the asymptotic null distribution, and examine the performance of the proposed joint test statistic via extensive simulations with a comparison to existing tests. The simulation results show that our method controls type I error properly and in general provides better power than existing test methods. We apply our method to examine whether a group of glucose metabolites and acetylamino acids mediate the effect of nutrient intakes on insulin resistance.

Authors who are presenting talks have a * after their name.

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