AVERAGE TREATMENT EFFECTS IN THE PRESENCE OF UNKNOWN INTERFERENCE.

AVERAGE TREATMENT EFFECTS IN THE PRESENCE OF UNKNOWN INTERFERENCE.
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存在未知干扰时的平均治疗效果。

DOI:
10.1214/20-aos1973
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发表时间:
2021-04
影响因子:
4.5
通讯作者:
Hudgens M
Hudgens M
中科院分区:
数学1区
文献类型:
--
作者:
Sävje F;Aronow P;Hudgens M

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我们在随机实验中研究了未知干扰下治疗效果估计量的大样本性质。推断目标是平均治疗效果估计量的泛化,其边缘化了潜在的溢出效应。我们发现,估计通常用于估计治疗效果下没有干扰是一致的广义估计几个常见的实验设计有限,但在其他任意和未知的干扰。收敛速率取决于干扰量增长的速率及其与治疗分配相关性的一致程度。重要的从业者,结果意味着,如果一个错误的假设,单位不干扰设置有限,甚至中度,干扰,标准估计仍然可能接近平均治疗效果,如果样本足够大。然而,传统的置信度声明可能并不准确。
We investigate large-sample properties of treatment effect estimators under unknown interference in randomized experiments. The inferential target is a generalization of the average treatment effect estimand that marginalizes over potential spillover effects. We show that estimators commonly used to estimate treatment effects under no interference are consistent for the generalized estimand for several common experimental designs under limited but otherwise arbitrary and unknown interference. The rates of convergence depend on the rate at which the amount of interference grows and the degree to which it aligns with dependencies in treatment assignment. Importantly for practitioners, the results imply that if one erroneously assumes that units do not interfere in a setting with limited, or even moderate, interference, standard estimators are nevertheless likely to be close to an average treatment effect if the sample is sufficiently large. Conventional confidence statements may, however, not be accurate.
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影响因子: 5.8
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