Limitless Regression Discontinuity
Limitless Regression Discontinuity
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无限回归不连续性
DOI：
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发表时间：
2014
影响因子：
2.4
通讯作者：
B. Hansen
中科院分区：
文献类型：
--
作者：
Adam C. Sales;B. Hansen
传统上，回归不连续性分析对比单变量回归的极限，因为其自变量R从任一侧接近切割点c。替代方法的目标是c附近小区域内的平均治疗效果，其代价是假设治疗分配IR < c相对维斯潜在结果是可预测的。相反，本文中提出的方法假设“剩余可验证性”，即治疗分配维斯于去趋势潜在结局的可验证性。去趋势的影响，而不是普通的最小二乘法，但与MM估计，以下一个不同的阶段的样品净化。该方法的推论承认在这两个调整的不确定性，尽管其适用性R是离散的或连续的，它是唯一强大的领导面临的回归不连续性设计的有效性威胁。
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.
关于社区干预试验的设计考虑和基于随机化的推断。
影响因子：
2
作者：
Gail,MH;Mark,SD;Carroll,RJ;Green,SB;Pee,D
通讯作者：
Pee,D