A0904
Title: Heterogeneous treatment and spillover effects under network interference
Authors: Zhibing He - Yale University (United States) [presenting]
Laura Forastiere - Yale University (United States)
Abstract: Behavioral health interventions, such as trainings, are implemented in settings where individuals are interconnected, and the intervention assigned to some individuals may also affect others within their network. Evaluating such interventions requires assessing both the effect of the intervention on those who receive it and the spillover effect on those connected to the treated individuals. With behavioral interventions, spillover effects can be heterogeneous in that certain individuals, due to their social connectedness and individual characteristics, are more likely to respond to the intervention and influence their peers' behaviors. Targeting these individuals can improve the effectiveness of interventions in the population. The focus is on an egocentric network-based randomized trial (ENRT) design, where a set of index participants is recruited and randomly assigned to the treatment group, while concurrently collecting outcome data on their nominated network members, who remain untreated. A testing method, multiple comparison with best (MCB), is developed to identify subgroups of index participants who receive the intervention and exhibit the largest spillover effect on their network members. The proposed methods are demonstrated in a study on a network-based peer HIV prevention education program, providing insights into strategies for selecting peer educators in peer education interventions.
