2 citations · 2 across the 7 of their papers we have counts for
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Model-Based Regression Adjustment with Model-Free Covariates for Network Interference
Kevin Han, Johan Ugander
When estimating a Global Average Treatment Effect (GATE) under network interference, units can have widely different relationships to the treatment depending on a combination of th…
Detecting Interference in A/B Testing with Increasing Allocation
Kevin Han, Shuangning Li, Jialiang Mao +1
In the past decade, the technology industry has adopted online randomized controlled experiments (a.k.a. A/B testing) to guide product development and make business decisions. In p…
Ensemble Method for Estimating Individualized Treatment Effects
Kevin Wu Han, Han Wu
In many medical and business applications, researchers are interested in estimating individualized treatment effects using data from a randomized experiment. For example in medical…
Estimating Treatment Effects Using Observational Data and Experimental Data with Non-overlapping Support
Kevin Han
When estimating treatment effects, the golden standard is to conduct a randomized experiment and then contrast outcomes associated with the treatment group and the control group. H…
Population Interference in Panel Experiments
Kevin Han, Iavor Bojinov, Guillaume Basse
The phenomenon of population interference, where a treatment assigned to one experimental unit affects another experimental unit's outcome, has received considerable attention in s…