A General Method for Detecting Interference Between Units in Randomized Experiments

Abstract

Interference between units may pose a threat to unbiased causal inference in randomized controlled experiments. Although the assumption of no interference is often necessary for causal inference, few options are available for testing this assumption. This article presents an ex post method for detecting interference between units in randomized experiments. With a test statistic of the analyst’s choice, a conditional randomization test allows for the calculation of the exact significance level of the causal dependence of outcomes on the treatment status of other units. The robustness of the method is demonstrated through simulation studies. Moreover, using this method, interference between units is detected in a field experiment designed to assess the effect of mailings on voter turnout in a U.S. primary election.