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stat.ME2026
GAAVI: Global Asymptotic Anytime Valid Inference for the Conditional Mean Function
Brian M Cho, Raaz Dwivedi, Nathan Kallus
Inference on the conditional mean function (CMF) is central to tasks from adaptive experimentation to optimal treatment assignment and algorithmic fairness auditing. In this work,…
stat.ME2025
Efficient Adaptive Experimentation with Noncompliance
Miruna Oprescu, Brian M Cho, Nathan Kallus
We study the problem of estimating the average treatment effect (ATE) in adaptive experiments where treatment can only be encouraged -- rather than directly assigned -- via a binar…
stat.ME2025
Simulation-Based Inference for Adaptive Experiments
Brian M Cho, Aurélien Bibaut, Nathan Kallus
Multi-arm bandit experimental designs are increasingly being adopted over standard randomized trials due to their potential to improve outcomes for study participants, enable faste…