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Title: Adaptive bootstrap tests for composite null hypotheses in the mediation pathway analysis
Abstract

Mediation analysis aims to assess if, and how, a certain exposure influences an outcome of interest through intermediate variables. This problem has recently gained a surge of attention due to the tremendous need for such analyses in scientific fields. Testing for the mediation effect (ME) is greatly challenged by the fact that the underlying null hypothesis (i.e. the absence of MEs) is composite. Most existing mediation tests are overly conservative and thus underpowered. To overcome this significant methodological hurdle, we develop an adaptive bootstrap testing framework that can accommodate different types of composite null hypotheses in the mediation pathway analysis. Applied to the product of coefficients test and the joint significance test, our adaptive testing procedures provide type I error control under the composite null, resulting in much improved statistical power compared to existing tests. Both theoretical properties and numerical examples of the proposed methodology are discussed.

 
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Award ID(s):
2150601 1846747
NSF-PAR ID:
10473988
Author(s) / Creator(s):
; ;
Publisher / Repository:
Oxford University Press
Date Published:
Journal Name:
Journal of the Royal Statistical Society Series B: Statistical Methodology
Volume:
86
Issue:
2
ISSN:
1369-7412
Format(s):
Medium: X Size: p. 411-434
Size(s):
["p. 411-434"]
Sponsoring Org:
National Science Foundation
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