Testing High-Dimensional Mediation Effect with Arbitrary Exposure-Mediator Coefficients
Yinan Lin, Zijian Guo, Baoluo Sun, Zhenhua Lin

TL;DR
This paper introduces a novel high-dimensional mediation test that remains valid under all null hypotheses, including complex cases, without structural assumptions on exposure-mediator effects, demonstrated through simulations and real data.
Contribution
It proposes the first high-dimensional mediation test valid under all null cases and without structural assumptions on exposure-mediator coefficients.
Findings
Test is valid under all null cases including strong effects
Test demonstrates consistency and good performance in simulations
Application shows relevance to DNA methylation and lung cancer
Abstract
In response to the unique challenge created by high-dimensional mediators in mediation analysis, this paper presents a novel procedure for testing the nullity of the mediation effect in the presence of high-dimensional mediators. The procedure incorporates two distinct features. Firstly, the test remains valid under all cases of the composite null hypothesis, including the challenging scenario where both exposure-mediator and mediator-outcome coefficients are zero. Secondly, it does not impose structural assumptions on the exposure-mediator coefficients, thereby allowing for an arbitrarily strong exposure-mediator relationship. To the best of our knowledge, the proposed test is the first of its kind to provably possess these two features in high-dimensional mediation analysis. The validity and consistency of the proposed test are established, and its numerical performance is showcased…
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Taxonomy
TopicsGene Regulatory Network Analysis · DNA and Nucleic Acid Chemistry · Advanced biosensing and bioanalysis techniques
