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stat.ME2022★ 2 cited
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…
stat.ME2022
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…
stat.ME2022
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…