12 citations · 41 across the 11 of their papers we have counts for
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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.ME2021
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…