3 papers
stat.ME2026
Estimating the Average Treatment Effect under Limited Overlap via Polynomial Approximation and Extrapolation
Shunichiro Orihara, Sho Komukai, Fan Li
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 pr…
stat.ME2026
Demystify Doubly-Robust Estimation: The Role of Overlap
Chengxin Yang, Laine E. Thomas, Fan Li
The doubly-robust (DR) estimator is popular for evaluating causal effects in observational studies and is often perceived as more desirable than inverse probability weighting (IPW)…
stat.ME2026
What is Overlap Weighting, How Has it Evolved, and When to Use It for Causal Inference?
Haidong Lu, Fan Li, Laine E. Thomas
The growing availability of large health databases has expanded the use of observational studies for comparative effectiveness research. Unlike randomized trials, observational stu…