论文标题
调整在连续暴露在二进制曝光状态下的连续暴露环境中的空间混杂
Adjustment for Unmeasured Spatial Confounding in Settings of Continuous Exposure Conditional on the Binary Exposure Status: Conditional Generalized Propensity Score-Based Spatial Matching
论文作者
论文摘要
当存在未衡量的空间混淆时，倾向评分（PS）匹配与暴露的因果关系估计效应是偏差的。某些暴露是连续的，但取决于二进制变量（例如，从住宅（二进制）指定半径内的污染物（连续）水平）。此外，未测量的空间混杂可能因连续和二元属性的空间模式而异。我们为此类设置提出了一种新的广义倾向分数（GPS）匹配方法，称为条件GPS（CGPS）基于基于的空间匹配（CGPSSM）。一个激励的例子是调查与高石油生产和炼油（PPR）的炼油厂的邻近度之间的关联，并在美国东南部的中风普遍存在。 CGPSSM通过其空间接近度和与空间信息集成的GPS匹配暴露的观测单位（例如，暴露的参与者）与未暴露的单位相匹配。通过单独估计二元状态（暴露与未暴露）和CGP的二进制状态的PS来估计GPS。 CGPSSM维持PS匹配和空间分析的显着优势：对协变量平衡和调整的直接评估，以调整未测量的空间混淆。模拟表明，CGPSSM可以调整未测量的空间混杂。使用我们的示例，我们发现PPR与中风患病率之间的正相关。我们的R软件包CGPSSpatialMatch已公开可用。
Propensity score (PS) matching to estimate causal effects of exposure is biased when unmeasured spatial confounding exists. Some exposures are continuous yet dependent on a binary variable (e.g., level of a contaminant (continuous) within a specified radius from residence (binary)). Further, unmeasured spatial confounding may vary by spatial patterns for both continuous and binary attributes of exposure. We propose a new generalized propensity score (GPS) matching method for such settings, referred to as conditional GPS (CGPS)-based spatial matching (CGPSsm). A motivating example is to investigate the association between proximity to refineries with high petroleum production and refining (PPR) and stroke prevalence in the southeastern United States. CGPSsm matches exposed observational units (e.g., exposed participants) to unexposed units by their spatial proximity and GPS integrated with spatial information. GPS is estimated by separately estimating PS for the binary status (exposed vs. unexposed) and CGPS on the binary status. CGPSsm maintains the salient benefits of PS matching and spatial analysis: straightforward assessments of covariate balance and adjustment for unmeasured spatial confounding. Simulations showed that CGPSsm can adjust for unmeasured spatial confounding. Using our example, we found positive association between PPR and stroke prevalence. Our R package, CGPSspatialmatch, has been made publicly available.
