Adjusting for Peer-Influence in Propensity Scoring When Estimating Treatment Effects

Analyses of treatments, experiments, policies, and observational data, are confounded when people's treatment outcomes and/or participation decisions are influenced by those of their friends and acquaintances. This invalidates standard matching techniques as estimation tools. For instance, the vaccination decisions of a person's peers affect the person's choice to vaccinate as well as the probability that the person is exposed to a disease (violating the usual Stable Unit Treatment Value Assumption). We account for these interferences by explicitly modeling peer interaction in treatment participation decisions and then balance matchings accordingly. We incorporate this approach into one of the most common techniques used to evaluate treatment effects---propensity score matching---and provide asymptotic results. Two applications show that peer-influenced propensity score matching gives more accurate results than standard propensity score matching in the estimation of the effectiveness of vaccinations as well as the impact ofexercise participation on depression