A comparison of methods to estimate the hazard ratio under conditions of time-varying confounding and nonpositivity.
A comparison of methods to estimate the hazard ratio under conditions of time-varying confounding and nonpositivity.
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DOI：
10.1097/ede.0b013e31822549e8
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发表时间：
2011-09
期刊：
影响因子：
--
通讯作者：
Richardson DB
中科院分区：
文献类型：
--
作者：
Naimi AI;Cole SR;Westreich DJ;Richardson DB
在职业流行病学研究中，卫生工作者幸存者效应是指导致累积暴露与健康结果之间关联估计偏差的过程。在这些环境中，工作状态作为一个中间和混杂变量，并可能违反积极性假设（暴露和未暴露的观察结果在所有层次的混杂因素的存在）。使用蒙特卡罗模拟，我们评估的程度，原油，工作状态调整，加权（边际结构）考克斯比例风险模型是有偏见的存在下随时间变化的混杂和非阳性。我们模拟代表随时间变化的职业暴露，工作状态和死亡率的数据。在一系列情景中，相对于真实的边际暴露效应计算偏倚、覆盖率和均方根误差（MSE）。对于基础情况，分别使用粗、调整和加权考克斯模型，风险比向下偏倚19%、9%和6%; 95%置信区间覆盖率为48%、85%和91%;根MSE为0.20、0.13和0.11。尽管边际结构模型在大多数研究场景中的偏倚较小，但标准或边际结构考克斯比例风险模型都不能完全解决时变混杂和非阳性条件下遇到的偏倚。
In occupational epidemiologic studies, the healthy-worker survivor effect refers to a process that leads to bias in the estimates of an association between cumulative exposure and a health outcome. In these settings, work status acts both as an intermediate and confounding variable, and may violate the positivity assumption (the presence of exposed and unexposed observations in all strata of the confounder). Using Monte Carlo simulation, we assess the degree to which crude, work-status adjusted, and weighted (marginal structural) Cox proportional hazards models are biased in the presence of time-varying confounding and nonpositivity. We simulate data representing time-varying occupational exposure, work status, and mortality. Bias, coverage, and root mean squared error (MSE) were calculated relative to the true marginal exposure effect in a range of scenarios. For a base-case scenario, using crude, adjusted, and weighted Cox models, respectively, the hazard ratio was biased downward 19%, 9%, and 6%; 95% confidence interval coverage was 48%, 85%, and 91%; and root MSE was 0.20, 0.13, and 0.11. Although marginal structural models were less biased in most scenarios studied, neither standard nor marginal structural Cox proportional hazards models fully resolve the bias encountered under conditions of time-varying confounding and nonpositivity.