TY - JOUR
T1 - Estimation of indirect effect when the mediator is a censored variable
AU - Wang, Jian
AU - Shete, Sanjay
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Jian Wang was supported, in part, by the National Institutes of Health (NIH), grant R03CA192197. Sanjay Shete was supported, in part, by the NIH grants 1R01CA131324, R01DE022891, and R25DA026120; the Cancer Prevention Research Institute of Texas grant RP130123, and the Barnhart Family Distinguished Professorship in Targeted Therapy. Jian Wang and Sanjay Shete were supported, in part, by the Cancer Center Support Grant P30CA016672. The MESA project is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, and CTSA UL1-RR-024156. The MESA CARe data used for the analyses described in this manuscript were obtained through dbGaP (phs000209.v13.p3). Funding for CARe genotyping was provided by NHLBI Contract N01-HC-65226.
Publisher Copyright:
© The Author(s) 2017.
PY - 2018/10/1
Y1 - 2018/10/1
N2 - A mediation model explores the direct and indirect effects of an initial variable (X) on an outcome variable (Y) by including a mediator (M). In many realistic scenarios, investigators observe censored data instead of the complete data. Current research in mediation analysis for censored data focuses mainly on censored outcomes, but not censored mediators. In this study, we proposed a strategy based on the accelerated failure time model and a multiple imputation approach. We adapted a measure of the indirect effect for the mediation model with a censored mediator, which can assess the indirect effect at both the group and individual levels. Based on simulation, we established the bias in the estimations of different paths (i.e. the effects of X on M [a], of M on Y [b] and of X on Y given mediator M [c’]) and indirect effects when analyzing the data using the existing approaches, including a naïve approach implemented in software such as Mplus, complete-case analysis, and the Tobit mediation model. We conducted simulation studies to investigate the performance of the proposed strategy compared to that of the existing approaches. The proposed strategy accurately estimates the coefficients of different paths, indirect effects and percentages of the total effects mediated. We applied these mediation approaches to the study of SNPs, age at menopause and fasting glucose levels. Our results indicate that there is no indirect effect of association between SNPs and fasting glucose level that is mediated through the age at menopause.
AB - A mediation model explores the direct and indirect effects of an initial variable (X) on an outcome variable (Y) by including a mediator (M). In many realistic scenarios, investigators observe censored data instead of the complete data. Current research in mediation analysis for censored data focuses mainly on censored outcomes, but not censored mediators. In this study, we proposed a strategy based on the accelerated failure time model and a multiple imputation approach. We adapted a measure of the indirect effect for the mediation model with a censored mediator, which can assess the indirect effect at both the group and individual levels. Based on simulation, we established the bias in the estimations of different paths (i.e. the effects of X on M [a], of M on Y [b] and of X on Y given mediator M [c’]) and indirect effects when analyzing the data using the existing approaches, including a naïve approach implemented in software such as Mplus, complete-case analysis, and the Tobit mediation model. We conducted simulation studies to investigate the performance of the proposed strategy compared to that of the existing approaches. The proposed strategy accurately estimates the coefficients of different paths, indirect effects and percentages of the total effects mediated. We applied these mediation approaches to the study of SNPs, age at menopause and fasting glucose levels. Our results indicate that there is no indirect effect of association between SNPs and fasting glucose level that is mediated through the age at menopause.
KW - Mediation analysis
KW - accelerated failure time
KW - censored mediator
KW - indirect effects
KW - multiple imputation
UR - http://www.scopus.com/inward/record.url?scp=85044047321&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85044047321&partnerID=8YFLogxK
U2 - 10.1177/0962280217690414
DO - 10.1177/0962280217690414
M3 - Article
C2 - 28132585
AN - SCOPUS:85044047321
SN - 0962-2802
VL - 27
SP - 3010
EP - 3025
JO - Statistical Methods in Medical Research
JF - Statistical Methods in Medical Research
IS - 10
ER -