Testing for Mediation Effect with Application to Human Microbiome Data

Haixiang Zhang, Jun Chen, Zhigang Li, Lei Liu

Research output: Contribution to journalArticle

Abstract

Mediation analysis has been commonly used to study the effect of an exposure on an outcome through a mediator. In this paper, we are interested in exploring the mediation mechanism of microbiome, whose special features make the analysis challenging. We consider the isometric logratio transformation of the relative abundance as the mediator variable. Then, we present a de-biased Lasso estimate for the mediator of interest and derive its standard error estimator, which can be used to develop a test procedure for the interested mediation effect. Extensive simulation studies are conducted to assess the performance of our method. We apply the proposed approach to test the mediation effect of human gut microbiome between the dietary fiber intake and body mass index.

Original languageEnglish (US)
JournalStatistics in Biosciences
DOIs
StateAccepted/In press - Jan 1 2019

Fingerprint

Mediation
Microbiota
Mediator
Testing
Dietary Fiber
Body Mass Index
Lasso
Error Estimator
Standard error
Isometric
Biased
Simulation Study
Fiber
Human
alachlor
Estimate
Gastrointestinal Microbiome

Keywords

  • Compositional mediators
  • High-dimensional data
  • Isometric logratio transformation
  • Joint significance test
  • Mediation analysis

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology (miscellaneous)

Cite this

Testing for Mediation Effect with Application to Human Microbiome Data. / Zhang, Haixiang; Chen, Jun; Li, Zhigang; Liu, Lei.

In: Statistics in Biosciences, 01.01.2019.

Research output: Contribution to journalArticle

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