混淆
调解
计量经济学
观测误差
因果模型
比例危险模型
集合(抽象数据类型)
计算机科学
统计
心理学
数学
社会学
社会科学
程序设计语言
作者
Yan Ying,Mingchen Ren,Alexander R. de Leon
标识
DOI:10.1080/03610918.2023.2170412
摘要
In the disciplines of medicine, biology and social science, causal mediation analysis is widely used to examine the effect of an exposure on an outcome through different causal pathways. Recently, there is rapid development of mediation analysis with survival data. An early work of Lange and Hansen proposed to identify the direct and indirect causal effects under the additive hazards model with a single mediator. However, inaccurate measurements of mediators and confounders may lead to biased causal effect estimation. We propose a measurement error correction approach to tackle measurement error in the mediators and confounders under the additive hazards model where multiple mediators are present. We apply the proposed corrected method to the ACTG175 Study data set, and uncover interesting findings.
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