Large Sample Randomization Inference of Causal Effects in the Presence of Interference

• Activity Number: 370
• Type: Contributed
• Date/Time: Tuesday, August 6, 2013 : 10:30 AM to 12:20 PM
• Sponsor: ENAR
• Author(s): Lan Liu*+ and Michael G. Hudgens
• Companies: UNC-CH and The University of North Carolina at Chapel Hill
• Keywords: causal inference ; confidence interval ; interference ; interference ; randomization

Abstract

Recently, increasing attention has focused on making causal inference when interference is possible. In the presence of interference, treatment may have several types of effects. In this paper, we consider inference about such effects when the population consists of groups of individuals where interference is possible within groups but not between groups. A two stage randomization design is assumed where in the first stage groups are randomized to different treatment allocation strategies and in the second stage individuals are randomized to treatment or control conditional on the strategy assigned to their group in the first stage. For this design, the asymptotic distributions of estimators of the causal effects are derived when either the number of individuals per group or the number of groups grows large. Under certain homogeneity assumptions, the asymptotic distributions provide justification