2 citations · 6 across the 9 of their papers we have counts for
4 papers · 1 filter
Rerandomization for quantile treatment effects
Tingxuan Han, Yuhao Wang
Although complete randomization is widely regarded as the gold standard for causal inference, covariate imbalance can still arise by chance in finite samples. Rerandomization has e…
Permutation Inference under Multi-way Clustering and Missing Data
Wenxuan Guo, Panos Toulis, Yuhao Wang
Econometric applications with multi-way clustering often feature a small number of effective clusters or heavy-tailed data, making standard cluster-robust and bootstrap inference u…
Adjusting auxiliary variables under approximate neighborhood interference
Xin Lu, Yuhao Wang, Zhiheng Zhang
Randomized experiments are the gold standard for causal inference. However, traditional assumptions, such as the Stable Unit Treatment Value Assumption (SUTVA), often fail in real-…
Debiased regression adjustment in completely randomized experiments with moderately high-dimensional covariates
Xin Lu, Fan Yang, Yuhao Wang
Completely randomized experiment is the gold standard for causal inference. When the covariate information for each experimental candidate is available, one typical way is to inclu…