We propose a model of treatment interference where the response of a unit depends only on its treatment status and the statuses of units within its K-neighborhood. Current methods for detecting interference include carefully designed randomized experiments and conditional randomization tests on a set of focal units. We give guidance on how to choose focal units under this model of interference. We then conduct a simulation study to evaluate the efficacy of existing methods for detecting network interference. We show that this choice of focal units leads to powerful tests of treatment interference which outperform current experimental methods.

翻译：我们提出一种处理效应干扰模型，其中研究单元的反应仅取决于其自身处理状态及k邻域内单元的处理状态。当前检测干扰的方法包括精心设计的随机实验以及对焦点单元组进行的条件随机化检验。本文针对该干扰模型下如何选择焦点单元提供指导性建议，随后开展仿真研究评估现有网络干扰检测方法的有效性。研究表明，该焦点单元选择策略可构建效力更强的处理效应干扰检测方案，其性能优于现有实验方法。