Sensitivity analysis for interactions under unmeasured confounding

被引:37
作者
VanderWeele, Tyler J. [1 ,2 ]
Mukherjee, Bhramar [3 ]
Chen, Jinbo [4 ]
机构
[1] Harvard Univ, Sch Publ Hlth, Dept Epidemiol, Boston, MA 02115 USA
[2] Harvard Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA
[3] Univ Michigan, Dept Biostat, Ann Arbor, MI 48109 USA
[4] Univ Penn, Dept Biostat, Philadelphia, PA 19104 USA
基金
美国国家卫生研究院;
关键词
bias analysis; gene environment; independence; interaction; sensitivity analysis; unmeasured confounding; LUNG-CANCER; SYNERGISM; SUSCEPTIBILITY; SMOKING; RISK;
D O I
10.1002/sim.4354
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
We develop a sensitivity analysis technique to assess the sensitivity of interaction analyses to unmeasured confounding. We give bias formulas for sensitivity analysis for interaction under unmeasured confounding on both additive and multiplicative scales. We provide simplified formulas in the case in which either one of the two factors does not interact with the unmeasured confounder in its effects on the outcome. An interesting consequence of the results is that if the two exposures of interest are independent (e.g., geneenvironment independence), even under unmeasured confounding, if the estimate of the interaction is nonzero, then either there is a true interaction between the two factors or there is an interaction between one of the factors and the unmeasured confounder; an interaction must be present in either scenario. We apply the results to two examples drawn from the literature. Copyright (c) 2011 John Wiley & Sons, Ltd.
引用
收藏
页码:2552 / 2564
页数:13
相关论文
共 26 条