论文标题
边缘结构模型的灵敏度分析
Sensitivity Analysis for Marginal Structural Models
论文作者
论文摘要
我们介绍了几种评估对边际结构模型中未衡量混杂的敏感性的方法；重要的是，我们允许治疗是离散或连续，静态或时间变化的。我们考虑了三个灵敏度模型：基于倾向的模型，基于结果的模型和一个子集混杂模型，其中只有一小部分人口受到无法衡量的混杂。在每种情况下，我们都会为因果参数的边界开发有效的估计器和置信区间。
We introduce several methods for assessing sensitivity to unmeasured confounding in marginal structural models; importantly we allow treatments to be discrete or continuous, static or time-varying. We consider three sensitivity models: a propensity-based model, an outcome-based model, and a subset confounding model, in which only a fraction of the population is subject to unmeasured confounding. In each case we develop efficient estimators and confidence intervals for bounds on the causal parameters.
