标题： 非参数方法用于连续治疗效果的双重稳健估计 显示英文标题

标题： Nonparametric methods for doubly robust estimation of continuous treatment effects

摘要： 连续性处理（例如剂量）在实际中经常出现，但许多可用的因果效应估计量要么需要对效应曲线进行参数化模型假设，要么不允许通过双重稳健的协变量调整。 我们开发了一种新颖的核平滑方法，该方法仅需对效应曲线进行适度的光滑性假设，并且仍然允许治疗密度或结果回归的误设。 我们推导了渐近性质并给出了数据驱动带宽选择的程序。 这些方法通过模拟研究和护士人员配置对医院再入院处罚影响的研究进行了说明。 显示英文摘要

摘要： Continuous treatments (e.g., doses) arise often in practice, but many available causal effect estimators are limited by either requiring parametric models for the effect curve, or by not allowing doubly robust covariate adjustment. We develop a novel kernel smoothing approach that requires only mild smoothness assumptions on the effect curve, and still allows for misspecification of either the treatment density or outcome regression. We derive asymptotic properties and give a procedure for data-driven bandwidth selection. The methods are illustrated via simulation and in a study of the effect of nurse staffing on hospital readmissions penalties.