4 citations · 4 across the 4 of their papers we have counts for
4 papers
When is it worthwhile to jackknife? Breaking the quadratic barrier for Z-estimators
Licong Lin, Fangzhou Su, Wenlong Mou +2
Resampling methods are especially well-suited to inference with estimators that provide only "black-box'' access. Jackknife is a form of resampling, widely used for bias correction…
A decorrelation method for general regression adjustment in randomized experiments
Fangzhou Su, Wenlong Mou, Peng Ding +1
We study regression adjustment with general function class approximations for estimating the average treatment effect in the design-based setting. Standard regression adjustment in…
When is the estimated propensity score better? High-dimensional analysis and bias correction
Fangzhou Su, Wenlong Mou, Peng Ding +1
Anecdotally, using an estimated propensity score is superior to the true propensity score in estimating the average treatment effect based on observational data. However, this clai…
Model-assisted analyses of cluster-randomized experiments
Fangzhou Su, Peng Ding
Cluster-randomized experiments are widely used due to their logistical convenience and policy relevance. To analyze them properly, we must address the fact that the treatment is as…