论文标题
双重稳健的非参数仪器可变估计器的生存结果
Doubly Robust Nonparametric Instrumental Variable Estimators for Survival Outcomes
论文作者
论文摘要
仪器变量（IV）方法使我们有机会解决因果推理中未得到的混杂问题。但是，大多数IV方法仅适用于离散或连续结果，而iv方法很少用于审查生存结果。在这项工作中，我们提出了对局部平均治疗效果对不可降至和可忽视的审查下生存概率的非参数估计量。当IV是二进制或连续时，我们提供了有效的基于影响功能的估计器和简单的估计过程。所提出的估计器具有双重的属性，并且可以使用机器学习工具轻松合并非参数估计。在模拟研究中，我们证明了在各种合理的情况下提出的估计量的灵活性和效率。我们将我们的方法应用于前列腺，肺，结直肠和卵巢癌筛查试验，以估算筛查对生存概率的因果关系，并研究不同审查假设下两种干预措施之间的因果关系。
Instrumental variable (IV) methods allow us the opportunity to address unmeasured confounding in causal inference. However, most IV methods are only applicable to discrete or continuous outcomes with very few IV methods for censored survival outcomes. In this work we propose nonparametric estimators for the local average treatment effect on survival probabilities under both nonignorable and ignorable censoring. We provide an efficient influence function-based estimator and a simple estimation procedure when the IV is either binary or continuous. The proposed estimators possess double-robustness properties and can easily incorporate nonparametric estimation using machine learning tools. In simulation studies, we demonstrate the flexibility and efficiency of our proposed estimators under various plausible scenarios. We apply our method to the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial for estimating the causal effect of screening on survival probabilities and investigate the causal contrasts between the two interventions under different censoring assumptions.
