Shunichiro Orihara

Estimating the average treatment effect under limited overlap via Polynomial Approximation and Extrapolation

Estimating the average treatment effect (ATE) remains a fundamental challenge in observational studies in the presence of poor or limited covariate overlap. Although the inverse probability weighting (IPW) estimator is a widely used approach for estimating the ATE, its performance can deteriorate substantially when ove...