Proximal mediation analysis
Proximal mediation analysis
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近端中介分析
DOI:
10.1093/biomet/asad015
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发表时间:
2023
期刊:
影响因子:
2.7
通讯作者:
Tchetgen Tchetgen, Eric J
中科院分区:
文献类型:
--
作者:
Dukes, Oliver;Shpitser, Ilya;Tchetgen Tchetgen, Eric J
A common concern when trying to draw causal inferences from observational data is that the measured covariates are insufficiently rich to account for all sources of confounding. In practice, many of the covariates may only be proxies of the latent confounding mechanism. Recent work has shown that in certain settings where the standard no-unmeasured-confounding assumption fails, proxy variables can be leveraged to identify causal effects. Results currently exist for the total causal effect of an intervention, but little consideration has been given to learning about the direct or indirect pathways of the effect through a mediator variable. In this work, we describe three separate proximal identification results for natural direct and indirect effects in the presence of unmeasured confounding. We then develop a semiparametric framework for inference on natural direct and indirect effects, which leads us to locally efficient, multiply robust estimators.
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DOI:
10.2139/ssrn.1423353
发表时间:
2009-06
期刊:
IZA Institute of Labor Economics Discussion Paper Series
影响因子:
--
作者:
Carlos A. Flores;Alfonso Flores-Lagunes
通讯作者:
Carlos A. Flores;Alfonso Flores-Lagunes
DOI:
10.1001/jama.2021.14075
发表时间:
2021-09-21
期刊:
JAMA
影响因子:
--
作者:
Lee H;Cashin AG;Lamb SE;Hopewell S;Vansteelandt S;VanderWeele TJ;MacKinnon DP;Mansell G;Collins GS;Golub RM;McAuley JH;AGReMA group;Localio AR;van Amelsvoort L;Guallar E;Rijnhart J;Goldsmith K;Fairchild AJ;Lewis CC;Kamper SJ;Williams CM;Henschke N
通讯作者:
Henschke N
DOI:
--
发表时间:
2018
期刊:
影响因子:
--
作者:
Wang Miao;E. Tchetgen
通讯作者:
E. Tchetgen
DOI:
--
发表时间:
2010
期刊:
影响因子:
--
作者:
P. Shrout;K. Keyes;K. Ornstein
通讯作者:
K. Ornstein
影响因子:
3.3
作者:
Shi X;Miao W;Tchetgen ET
通讯作者:
Tchetgen ET