TY - JOUR
T1 - Testing for Mediation Effect with Application to Human Microbiome Data
AU - Zhang, Haixiang
AU - Chen, Jun
AU - Li, Zhigang
AU - Liu, Lei
N1 - Publisher Copyright:
© 2019, International Chinese Statistical Association.
PY - 2021/7
Y1 - 2021/7
N2 - 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.
AB - 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.
KW - Compositional mediators
KW - High-dimensional data
KW - Isometric logratio transformation
KW - Joint significance test
KW - Mediation analysis
UR - http://www.scopus.com/inward/record.url?scp=85069842589&partnerID=8YFLogxK
U2 - 10.1007/s12561-019-09253-3
DO - 10.1007/s12561-019-09253-3
M3 - Article
C2 - 34093887
AN - SCOPUS:85069842589
SN - 1867-1764
VL - 13
SP - 313
EP - 328
JO - Statistics in Biosciences
JF - Statistics in Biosciences
IS - 2
ER -