3 papers
math.ST2026
Bootstrap consistency for general double/debiased machine learning estimators
Ziming Lin, Fang Han
Double/debiased machine learning (DML) provides a general framework for inference with high-dimensional or otherwise complex nuisance parameters by combining Neyman-orthogonal scor…
stat.ME2025
Stabilized Inverse Probability Weighting via Isotonic Calibration
Lars van der Laan, Ziming Lin, Marco Carone +1
Inverse weighting with an estimated propensity score is widely used by estimation methods in causal inference to adjust for confounding bias. However, directly inverting propensity…
math.ST2024
On the consistency of bootstrap for matching estimators
Ziming Lin, Fang Han
In a landmark paper, Abadie and Imbens (2008) showed that the naive bootstrap is inconsistent when applied to nearest neighbor matching estimators of the average treatment effect w…