3 papers
stat.ME2026
Estimating within-cluster and between-cluster spillover effects in randomized saturation designs
Sizhu Lu, Lei Shi, Peng Ding
Randomized saturation designs are two-stage experiments: they first randomly assign treatment probabilities over the clusters and then randomly assign the treatment to the units wi…
stat.ME2025
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…
math.ST2025
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…