Online Program Home
My Program

Abstract Details

Activity Number: 239
Type: Topic Contributed
Date/Time: Monday, August 1, 2016 : 2:00 PM to 3:50 PM
Sponsor: Health Policy Statistics Section
Abstract #320709
Title: Disentangling Bed Nets and Spillover Effects in a Clustered Encouragement Design for Malaria Control: A Bayesian Principal Stratification Approach
Author(s): Laura Forastiere* and Fabrizia Mealli and Tyler J. VanderWeele
Companies: University of Florence and University of Florence and Harvard
Keywords: Causal Inference ; Bayesian Analysis ; Causal Mechanisms ; Noncompliance ; Spillover Effects

Encouragement designs arise frequently with the purpose of increasing the uptake of the treatment of interest that cannot be enforced. By design, encouragements entail the complication of non-compliance and they can give rise to a variety of mechanisms. In particular, when they are assigned at cluster level social interactions can result in spillover effects. Disentangling the effect of encouragement through spillover effects from that through the enhancement of the treatment could be crucial for improving the program and planning the scale-up. We capitalize on the principal stratification framework to define stratum-specific causal effects, i.e., effects for specific latent subpopulations defined by the joint potential compliance statuses under both encouragement conditions. We provide alternative assumptions under which an extrapolation across principal strata allows to disentangle the effects. Estimation is performed using Bayesian hierarchical models to account for clustering. We illustrate the proposed methodology on a cluster randomized experiment implemented in Zambia to evaluate the impact on malaria prevalence of a loan program intended to increase bed net coverage.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2016 program

Copyright © American Statistical Association