In settings where interference between units is possible, we define the prevelance of peer effects to be the number of units who are affected by the treatment of others. This quantity does not fully identify a peer effect, but may be used to show whether peer effects are widely prevalent. Given a randomized experiment with binary-valued outcomes, methods are presented for conservative point estimation and one-sided interval estimation. To show asymptotic coverage of our intervals in settings not previously covered, we provide a central limit theorem that combines local dependence and sampling without replacement. Consistency and minimax properties of the point estimator are shown as well. The approach is demonstrated on an experiment in which students were treated for a highly transmissible parasitic infection, for which we find that a significant fraction of students were affected by the treatment of schools other than their own.

翻译：在单元间可能存在相互干扰的情境中，我们将同伴效应的普遍性定义为受他人处理影响的单元数量。该量度虽不能完全识别同伴效应，但可用于展示同伴效应是否广泛存在。针对二元结果变量的随机实验，本文提出了保守点估计和单侧区间估计的方法。为展示这些区间在以往未覆盖情境下的渐近覆盖性，我们提供了一个结合局部依赖性和无放回抽样的中心极限定理。同时证明了点估计量的一致性和极小极大性质。该方法在针对学生易感寄生虫感染的实验中得以验证，我们发现相当比例的学生受到了所在学校之外的学校处理的影响。