High-dimensional causal mediation analysis by partial sum statistic and sample splitting strategy in imaging genetics application.

ABSTRACT:

Summary

Causal mediation analysis investigates the role of mediators in the relationship between exposure and outcome. In the analysis of omics or imaging data, mediators are often high-dimensional, presenting challenges such as multicollinearity and interpretability. Existing methods either compromise interpretability or fail to effectively prioritize mediators. To address these challenges and advance causal mediation analysis in high-dimensional contexts, we propose the Partial Sum Statistic and Sample Splitting Strategy (PS5) framework. Through extensive simulations, we demonstrate that PS5 offers superior type I error control, higher statistical power, reduced bias in mediation effect estimation, and more accurate mediator selection. We apply PS5 to an imaging genetics dataset

SUBMITTER: Chang HC 

PROVIDER: S-EPMC12502916 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature