5 papers · 1 filter
Statistical Inference for Continuous Action Bandits
Raphael C Kim, Michele Santacatterina, Ramin Zabih +2
Statistical inference under adaptively collected data is becoming increasingly popular across e-commerce and mobile health. Many methods exist for discrete action settings, ranging…
Data-Adaptive and Model-Robust Covariate Adjustment for Time-to-Event Outcomes in Stratified Randomized Trials
Raphael C. Kim, Brian Gilbert, Ramin Zabih +2
Time-to-event outcomes are commonly used as primary endpoints in randomized clinical trials. Despite this, relatively little work incorporates baseline covariate information while…
Fair Policy Learning under Bipartite Network Interference: Learning Fair and Cost-Effective Environmental Policies
Raphael C. Kim, Rachel C. Nethery, Kevin L. Chen +1
Numerous studies have shown the harmful effects of airborne pollutants on human health. Vulnerable groups and communities often bear a disproportionately larger health burden due t…
Difference-in-Differences under Bipartite Network Interference: A Framework for Quasi-Experimental Assessment of the Effects of Environmental Policies on Health
Kevin L. Chen, Falco J. Bargagli-Stoffi, Raphael C. Kim +2
Pollution from coal-fired power plants has been linked to substantial health and mortality burdens in the US. In recent decades, federal regulatory policies have spurred efforts to…
Environmental Justice Implications of Power Plant Emissions Control Policies: Heterogeneous Causal Effect Estimation under Bipartite Network Interference
Kevin L. Chen, Falco J. Bargagli Stoffi, Raphael C. Kim +1
Emissions generators, such as coal-fired power plants, are key contributors to air pollution and thus environmental policies to reduce their emissions have been proposed. Furthermo…