Identification and estimation of causal peer effects using double negative controls for unmeasured network confounding

• 成果类型: Article
• 署名作者: Egami, Naoki; Tchetgen, Eric J. Tchetgen
• 署名单位: Columbia University; University of Pennsylvania; University of Pennsylvania
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• DOI: 10.1093/jrsssb/qkad132
• 发表日期: 2024
• 页码: 487-511
• 关键词: social network; variables; inference; contagion; BIAS

摘要

Identification and estimation of causal peer effects are challenging in observational studies for two reasons. The first is the identification challenge due to unmeasured network confounding, for example, homophily bias and contextual confounding. The second is network dependence of observations. We establish a framework that leverages a pair of negative control outcome and exposure variables (double negative controls) to non-parametrically identify causal peer effects in the presence of unmeasured network confounding. We then propose a generalised method of moments estimator and establish its consistency and asymptotic normality under an assumption about psi-network dependence. Finally, we provide a consistent variance estimator.