causal inference 1generative models 1hybrid synthesis 1synthetic data 1treatment effect estimation 1
From the 1 of 7 linked papers with an AI index.
Showing stat.MEShow all
3 papers · 1 filter
stat.ME2026
Generative Synthetic Data for Causal Inference: Pitfalls, Remedies, and Opportunities
Yichen Xu
The paper examines how fully generative synthetic data models can preserve predictive performance but distort causal estimates, and proposes a hybrid synthetic-data approach that s…
stat.ME2026
Adaptive Targeted Maximum Likelihood Estimation of the Mean Potential Outcome under a Treatment Rule
Yichen Xu, Mark J. van der Laan
Estimating the mean counterfactual outcome under a treatment rule is a central problem in causal inference and policy evaluation. Standard estimators, including inverse probability…
stat.ME2026
Investigating Targeting Strategies and Truncation in TMLE for the Average Treatment Effect under Practical Positivity Violations
Yichen Xu, Susan Gruber, Mark J. van der Laan
Estimating average treatment effects from observational data is challenging under practical violations of the positivity assumption. Targeted Maximum Likelihood Estimators (TMLEs)…