随机对照试验的聚类和外部效度

Antoine Deeb, Clément de Chaisemartin
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引用次数: 8

摘要

在研究随机对照试验(RCTs)的文献中,通常假设参与实验的单位的潜在结果是确定的。这个假设不太可能成立,因为在实验过程中可能会发生随机冲击。在本文中,我们考虑了具有个体水平治疗分配的随机对照试验的情况,并且我们允许个体水平和集群水平(例如村庄水平)的冲击影响潜在结果。我们表明,人们可以对两个估计作出推断:使用异方差鲁棒标准误差,以实现集群级冲击为条件的ATE;ATE利用簇鲁棒标准误差从这些冲击中剔除。通过聚类,研究人员可以测试如果实验中发生的随机冲击不同,治疗是否仍然有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Clustering and External Validity in Randomized Controlled Trials
In the literature studying randomized controlled trials (RCTs), it is often assumed that the potential outcomes of units participating in the experiment are deterministic. This assumption is unlikely to hold, as stochastic shocks may take place during the experiment. In this paper, we consider the case of an RCT with individual-level treatment assignment, and we allow for individual-level and cluster-level (e.g. village-level) shocks to affect the potential outcomes. We show that one can draw inference on two estimands: the ATE conditional on the realizations of the cluster-level shocks, using heteroskedasticity-robust standard errors; the ATE netted out of those shocks, using cluster-robust standard errors. By clustering, researchers can test if the treatment would still have had an effect, had the stochastic shocks that occurred during the experiment been different.
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