DFW: A Novel Weighting Scheme for Covariate Balancing and Treatment Effect Estimation
DFW:用于协变量平衡与处理效应估计的新加权方案
Estimating causal effects from observational data is challenging due to selection bias, which leads to imbalanced covariate distributions across treatment groups. Propensity score-based weighting methods are widely used to address this issue by reweighting samples to simulate a randomized controlled trial (RCT). However, the effectiveness of these methods heavily depends on the observed data and the accuracy of the propensity score estimator. For example, inverse propensity…