4 papers
Design-based theory for causal inference
Xin Lu, Wanjia Fu, Hongzi Li +4
Causal inference, as a major research area in statistics and data science, plays a central role across diverse fields such as medicine, economics, education, and the social science…
Conditional cross-fitting for unbiased machine-learning-assisted covariate adjustment in randomized experiments
Xin Lu, Lei Shi, Hanzhong Liu +1
Randomized experiments are the gold standard for estimating the average treatment effect (ATE). While covariate adjustment can reduce the asymptotic variances of the unbiased Horvi…
Rerandomization for covariate balance mitigates -hacking caused by strategically selecting covariates in regression adjustment
Xin Lu, Peng Ding
Rerandomization enforces covariate balance across treatment groups in the design stage of experiments. Despite its intuitive appeal, its theoretical justification remains unsatisfy…
Estimation and inference of average treatment effects under heterogeneous additive treatment effect model
Xin Lu, Hongzi Li, Hanzhong Liu
Randomized experiments are the gold standard for estimating treatment effects, yet network interference challenges the validity of traditional estimators by violating the stable un…