2 citations · 3 across the 2 of their papers we have counts for
3 papers
stat.ME2021★ 2 cited
To adjust or not to adjust? Estimating the average treatment effect in randomized experiments with missing covariates
Anqi Zhao, Peng Ding
Complete randomization allows for consistent estimation of the average treatment effect based on the difference in means of the outcomes without strong modeling assumptions on the…
stat.ME2021
Reconciling design-based and model-based causal inferences for split-plot experiments
Anqi Zhao, Peng Ding
The split-plot design assigns different interventions at the whole-plot and sub-plot levels, respectively, and induces a group structure on the final treatment assignments. A commo…
stat.ME2016
Randomization-Based Causal Inference from Unbalanced 2^2 Split-Plot Designs
Anqi Zhao, Peng Ding, Tirthankar Dasgupta
Given two 2-level factors of interest, a 2^2 split-plot design} (a) takes each of the possible factorial combinations as a treatment, (b) identifies one factor as `whole-pl…