Conventionally, regression discontinuity analysis contrasts a univariate regression’s limits as its independent variable, R, approaches a cut point, c, from either side. Alternative methods target the average treatment effect in a small region around c, at the cost of an assumption that treatment assignment, I R < c , is ignorable vis-à-vis potential outcomes. Instead, the method presented in this article assumes “residual ignorability,” ignorability of treatment assignment vis-à-vis detrended potential outcomes. Detrending is effected not with ordinary least squares but with MM estimation, following a distinct phase of sample decontamination. The method’s inferences acknowledge uncertainty in both of these adjustments, despite its applicability whether R is discrete or continuous; it is uniquely robust to leading validity threats facing regression discontinuity designs.

中文翻译：

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无限回归不连续

按照惯例，回归不连续性分析会对比单变量回归的极限，因为其自变量R从任一侧接近切入点c。替代方法针对c周围小区域的平均治疗效果，但前提是假设治疗分配IR <c对于潜在结果而言是可忽略的。取而代之的是，本文中介绍的方法假定“残余可燃性”，即相对于趋势恶化的潜在结果，治疗分配的可燃性。在样品去污的不同阶段之后，去趋势化不是通过普通的最小二乘法进行的，而是通过MM估计进行的。尽管R无论是离散的还是连续的，该方法的推论都承认这两个调整都存在不确定性。