Testing for Mediation Effect with Application to Human Microbiome Data

Haixiang Zhang, Jun Chen, Zhigang Li, Lei Liu

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

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)
Pages (from-to)313-328
Number of pages16
JournalStatistics in Biosciences
Volume13
Issue number2
DOIs
StatePublished - Jul 2021

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)

Fingerprint

Dive into the research topics of 'Testing for Mediation Effect with Application to Human Microbiome Data'. Together they form a unique fingerprint.

Cite this