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Causal Proportional Hazards Estimation with a Binary Instrumental Variable.
Statistica Sinica ( IF 1.5 ) Pub Date : 2022-1-1 , DOI: 10.5705/ss.202019.0096
Behzad Kianian 1 , Jung In Kim 2 , Jason P Fine 1 , Limin Peng 1
Affiliation  

Instrumental variables (IV) are a useful tool for estimating causal effects in the presence of unmeasured confounding. IV methods are well developed for uncensored outcomes, particularly for structural linear equation models, where simple two-stage estimation schemes are available. The extension of these methods to survival settings is challenging, partly because of the nonlinearity of the popular survival regression models and partly because of the complications associated with right censoring or other survival features. Motivated by the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer screening trial, we develop a simple causal hazard ratio estimator in a proportional hazards model with right censored data. The method exploits a special characterization of IV which enables the use of an intuitive inverse weighting scheme that is generally applicable to more complex survival settings with left truncation, competing risks, or recurrent events. We rigorously establish the asymptotic properties of the estimators, and provide plug-in variance estimators. The proposed method can be implemented in standard software, and is evaluated through extensive simulation studies. We apply the proposed IV method to a data set from the Prostate, Lung, Colorectal and Ovarian cancer screening trial to delineate the causal effect of flexible sigmoidoscopy screening on colorectal cancer survival which may be confounded by informative noncompliance with the assigned screening regimen.

中文翻译:

使用二元工具变量进行因果比例风险估计。

工具变量 (IV) 是一种有用的工具,可用于在存在未测量混杂的情况下估计因果效应。IV 方法非常适用于未经审查的结果,特别是对于结构线性方程模型,其中可以使用简单的两阶段估计方案。将这些方法扩展到生存环境具有挑战性,部分原因是流行的生存回归模型的非线性,部分原因是与右删失或其他生存特征相关的并发症。受前列腺、肺、结直肠和卵巢 (PLCO) 癌症筛查试验的启发,我们在具有右删失数据的比例风险模型中开发了一个简单的因果风险比估计器。该方法利用了 IV 的特殊特征,它能够使用直观的逆加权方案,该方案通常适用于具有左截断、竞争风险或复发事件的更复杂的生存设置。我们严格建立了估计量的渐近性质,并提供了插件方差估计量。所提出的方法可以在标准软件中实现,并通过广泛的模拟研究进行评估。我们将提议的 IV 方法应用于来自前列腺癌、肺癌、结直肠癌和卵巢癌筛查试验的数据集,以描绘灵活的乙状结肠镜筛查对结直肠癌存活率的因果影响,这可能会因信息不符合指定的筛查方案而混淆。或反复发生的事件。我们严格建立了估计量的渐近性质,并提供了插件方差估计量。所提出的方法可以在标准软件中实现,并通过广泛的模拟研究进行评估。我们将提议的 IV 方法应用于来自前列腺癌、肺癌、结直肠癌和卵巢癌筛查试验的数据集,以描绘灵活的乙状结肠镜筛查对结直肠癌存活率的因果影响,这可能会因信息不符合指定的筛查方案而混淆。或反复发生的事件。我们严格建立了估计量的渐近性质,并提供了插件方差估计量。所提出的方法可以在标准软件中实现,并通过广泛的模拟研究进行评估。我们将提议的 IV 方法应用于来自前列腺癌、肺癌、结直肠癌和卵巢癌筛查试验的数据集,以描绘灵活的乙状结肠镜筛查对结直肠癌存活率的因果影响,这可能会因信息不符合指定的筛查方案而混淆。
更新日期:2022-01-01
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