Estimation and inference of average treatment effects under heterogeneous additive treatment effect model

Randomized experiments are the gold standard for estimating treatment effects, yet network interference challenges the validity of traditional estimators by violating the stable unit treatment value assumption and introducing bias. While cluster randomized experiments mitigate this bias, they encoun...

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Veröffentlicht in:	arXiv.org 2024-08
Hauptverfasser:	Lu, Xin, Li, Hongzi, Liu, Hanzhong
Format:	Artikel
Sprache:	eng
Schlagworte:	Asymptotic methods Asymptotic properties Bias Eigenvectors Estimation Estimators Inference Local interference Normality Parameter robustness Regression models Stochastic processes
Online-Zugang:	Volltext
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