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Global test for high-dimensional mediation: Testing groups of potential mediators.

Vera DjordjilovićChristian M PageJon Michael GranTherese H NøstTorkjel M SandangerMarit B VeierødMagne Thoresen
Published in: Statistics in medicine (2019)
We address the problem of testing whether a possibly high-dimensional vector may act as a mediator between some exposure variable and the outcome of interest. We propose a global test for mediation, which combines a global test with the intersection-union principle. We discuss theoretical properties of our approach and conduct simulation studies that demonstrate that it performs equally well or better than its competitor. We also propose a multiple testing procedure, ScreenMin, that provides asymptotic control of either familywise error rate or false discovery rate when multiple groups of potential mediators are tested simultaneously. We apply our approach to data from a large Norwegian cohort study, where we look at the hypothesis that smoking increases the risk of lung cancer by modifying the level of DNA methylation.
Keyphrases
  • dna methylation
  • social support
  • gene expression
  • genome wide
  • high throughput
  • electronic health record
  • big data
  • smoking cessation
  • copy number
  • climate change
  • deep learning