 Post‐selection inference for high‐dimensional mediation analysis with survival outcomesTzu‐Jung Huang, Zhonghua Liu and Ian W. McKeague Scandinavian Journal of Statistics, 2025, vol. 52, issue 2, 756-776 Abstract: It is of substantial scientific interest to detect mediators that lie in the causal pathway from an exposure to a survival outcome. However, with high‐dimensional mediators, as often encountered in modern genomic data settings, there is a lack of powerful methods that can provide valid post‐selection inference for the identified marginal mediation effect. To resolve this challenge, we develop a post‐selection inference procedure for the maximally selected natural indirect effect using a semiparametric efficient influence function approach. To this end, we establish the asymptotic normality of a stabilized one‐step estimator that takes the selection of the mediator into account. Simulation studies show that our proposed method has good empirical performance. We further apply our proposed approach to a lung cancer dataset and find multiple DNA methylation CpG sites that might mediate the effect of cigarette smoking on lung cancer survival. Date: 2025 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:scjsta:v:52:y:2025:i:2:p:756-776 Ordering information: This journal article can be ordered from Access Statistics for this article Scandinavian Journal of Statistics is currently edited by ÿrnulf Borgan and Bo Lindqvist More articles in Scandinavian Journal of Statistics from Danish Society for Theoretical Statistics, Finnish Statistical Society, Norwegian Statistical Association, Swedish Statistical Association |
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