A novel strategy for detecting multiple mediators in high-dimensional mediation models.

ABSTRACT: This article presents a novel methodology for detecting multiple biomarkers in high-dimensional mediation models by utilizing a modified Least Absolute Shrinkage and Selection Operator (LASSO) alongside Pathway LASSO. This approach effectively addresses the problem of overestimating direct effects, which can result in the inaccurate identification of mediators with nonzero indirect effects. To mitigate this overestimation and improve the true positive rate for detecting mediators, two constraints on the L ₁-norm penalty are introduced. The effectiveness of the proposed methodology is demonstrated via extensive simulations across various scenarios and compared against other popular mediation methods, highlighting its robustness and reliability under different conditions. F

SUBMITTER: Yen PS 

PROVIDER: S-EPMC12745155 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature