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：我们提出了一种处理效应干扰模型，在该模型中，样本单元的响应仅取决于其自身的处理状态及其K邻域内其他单元的处理状态。当前检测干扰的方法包括精心设计的随机化实验和针对一组焦点单元的条件随机化检验。我们针对该干扰模型给出了焦点单元的选择指南。随后通过模拟研究评估了现有网络干扰检测方法的有效性。研究表明，我们提出的焦点单元选择策略能够构建出比现有实验方法更具效力的处理效应干扰检验。