Treatment effect estimation with observational network data using machine learning

Causal inference methods for treatment effect estimation usually assume independent units. However, this assumption is often questionable because units may interact, resulting in spillover effects between them. We develop augmented inverse probability weighting (AIPW) for estimation and inference of...

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Bibliographic Details
Main Authors: Emmenegger Corinne, Spohn Meta-Lina, Elmer Timon, Bühlmann Peter
Format: Article
Language:English
Published: De Gruyter 2025-04-01
Series:Journal of Causal Inference
Subjects:
Online Access:https://doi.org/10.1515/jci-2023-0082
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