21 citations · 38 across the 13 of their papers we have counts for
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stat.ME2022★ 1 cited
A Nonparametric Framework for Universal Difference-in-Differences
Chan Park, Eric Tchetgen Tchetgen
Difference-in-differences (DiD) is a popular approach to evaluate treatment effects in settings where both pre- and post-treatment measurements of the outcome are available. Despit…
stat.ME2022★ 21 cited
Model-robust and efficient covariate adjustment for cluster-randomized experiments
Bingkai Wang, Chan Park, Dylan S. Small +1
Cluster-randomized experiments are increasingly used to evaluate interventions in routine practice conditions, and researchers often adopt model-based methods with covariate adjust…
stat.ME2022
Propensity Score Modeling: Key Challenges When Moving Beyond the No-Interference Assumption
Hyunseung Kang, Chan Park, Ralph Trane
The paper presents some models for the propensity score. Considerable attention is given to a recently popular, but relatively under-explored setting in causal inference where the…