5 papers · 1 filter
Reorganizing Graduate Statistical Inference for Modern Biostatistical Practice
Raphael C Kim, Michele Santacatterina
First-year graduate courses in statistical inference within PhD programs in biostatistics often follow a classical mathematical statistics progression through probability models, d…
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…
Are Good Generators Good Decision-Makers? Policy Learning for General Interventions via Retargeted Counterfactual Generation
Raphael C Kim, Jingsen Zhu, Ramin Zabih +1
Generative models are increasingly used to support decision-making in complex systems, where interventions may be joint and high-dimensional, and outcomes are high-dimensional. How…
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…