1 citations · 2 across the 4 of their papers we have counts for
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Difference-in-differences with stochastic policy shifts of a continuous treatment
Michael Jetsupphasuk, Chenwei Fang, Didong Li +1
Treatment effects of stochastic policy shifts quantify differences in outcomes across counterfactual scenarios with varying treatment distributions. Stochastic policy shifts may be…
Efficient nonparametric estimation with difference-in-differences in the presence of network dependence and interference
Michael Jetsupphasuk, Didong Li, Michael G. Hudgens
Differences-in-differences (DiD) is a causal inference method for observational longitudinal data that assumes parallel expected potential outcome trajectories between treatment gr…
Finite sample performance of optimal treatment rule estimators with right-censored outcomes
Michael Jetsupphasuk, Michael G. Hudgens, Jessie K. Edwards +1
Patient care may be improved by recommending treatments based on patient characteristics when there is treatment effect heterogeneity. Recently, there has been a great deal of atte…
Causal Inference in Longitudinal Data under Unknown Interference
Ye Wang, Michael Jetsupphasuk
In longitudinal studies where units are embedded in space or a social network, interference may arise, meaning that a unit's outcome can depend on treatment histories of others. Th…