Revisiting the Effects of Maternal Education on Adolescents' Academic Performance: Doubly Robust Estimation in a Network-Based Observational Study
Vanessa McNealis, Erica E. M. Moodie, Nema Dean

TL;DR
This study develops doubly robust estimators to assess the causal effect of maternal education on adolescents' academic performance within social networks, addressing interference issues and demonstrating improved efficiency over traditional methods.
Contribution
It introduces a novel doubly robust estimation approach for causal inference in networked observational studies with interference, specifically applied to maternal education and adolescent performance.
Findings
No evidence of an indirect effect of maternal education within social circles.
DR estimators outperform IPW estimators in stability and efficiency.
Empirical validation of the DR property in a real social network setting.
Abstract
In many contexts, particularly when study subjects are adolescents, peer effects can invalidate typical statistical requirements in the data. For instance, it is plausible that a student's academic performance is influenced both by their own mother's educational level as well as that of their peers. Since the underlying social network is measured, the Add Health study provides a unique opportunity to examine the impact of maternal college education on adolescent school performance, both direct and indirect. However, causal inference on populations embedded in social networks poses technical challenges, since the typical no interference assumption no longer holds. While inverse probability-of-treatment weighted (IPW) estimators have been developed for this setting, they are often highly unstable. Motivated by the question of maternal education, we propose doubly robust (DR) estimators…
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Taxonomy
TopicsAdvanced Causal Inference Techniques · Statistical Methods and Inference
