ArticleJournal of the Royal Statistical Society. Series B, Statistical methodology2024
Adaptive bootstrap tests for composite null hypotheses in the mediation pathway analysis.
Article in Journal of the Royal Statistical Society. Series B, Statistical methodology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- The moderating effect of depression on social media use and online social support: differential effects on psychological well-being.BMC public health · 2026Article
- Estimating in silico causal effects of DNA methylation on gene expression through genetic anchors in airway epithelium in asthma.Science advances · 2026Article
- Development and Initial Validation of a Brief, Online Version of the Center for Epidemiological Studies Depression Scale (CES-D): Psychometric Study.JMIR formative research · 2026Article
- Adult attachment and intimate relationship satisfaction among university students: the chain mediating roles of appreciation and sense of giving.Frontiers in psychiatry · 2026Article
- From stress to exhaustion: the mediating role of meaning of work in the relationship between role conflict and emotional exhaustion among preschool teachers.Frontiers in psychology · 2026Article
- High-dimensional causal mediation analysis by partial sum statistic and sample splitting strategy in imaging genetics application.Bioinformatics (Oxford, England) · 2025Article
- The relationship between smartphone addiction and sleep quality in older adults: the mediating role of loneliness and depression.BMC nursing · 2025Article
- Causal Mediation Analysis for Integrating Exposure, Genomic, and Phenotype Data.Annual review of statistics and its application · 2025Article
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Authors and funding
3 authors.
Funding
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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