Amplification of Bias Due to Exposure Measurement Error.
Amplification of Bias Due to Exposure Measurement Error.
复制标题
由于曝光测量误差而导致的偏差放大。
DOI：
10.1093/aje/kwab228
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发表时间：
2022
影响因子：
5
通讯作者：
Cole,StephenR
中科院分区：
文献类型：
--
作者：
Richardson,DavidB;Keil,AlexanderP;Cole,StephenR
观察性流行病学研究通常面临暴露测量误差和混杂的挑战。考虑一项连续暴露与结果之间关联的观察性研究，其中主要关注的暴露变量存在经典测量误差（即，测量的曝光以独立误差分布在真实曝光周围）。在没有暴露测量误差的情况下，人们普遍认为应该控制感兴趣的相关性的混杂因素，以获得该暴露对感兴趣的结果的影响的无偏估计。然而，在这里，我们表明，在经典的暴露测量误差的存在下，净偏差的利益相关性的估计可能会增加调整后的混杂因素。我们提供了一个分析表达式，用于计算净偏差的变化，在经典的曝光测量误差的存在下，在调整混杂因素后，估计的相关性的兴趣，我们用模拟来说明这个问题。
Observational epidemiologic studies typically face challenges of exposure measurement error and confounding. Consider an observational study of the association between a continuous exposure and an outcome, where the exposure variable of primary interest suffers from classical measurement error (i.e., the measured exposures are distributed around the true exposure with independent error). In the absence of exposure measurement error, it is widely recognized that one should control for confounders of the association of interest to obtain an unbiased estimate of the effect of that exposure on the outcome of interest. However, here we show that, in the presence of classical exposure measurement error, the net bias in an estimate of the association of interest may increase upon adjustment for confounders. We offer an analytical expression for calculating the change in net bias in an estimate of the association of interest upon adjustment for a confounder in the presence of classical exposure measurement error, and we illustrate this problem using simulations.