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stat.ME2026
Transporting treatment effects by calibrating large-scale observational outcomes
Harrison H Li
A high-quality experimental dataset is often much smaller than a corresponding observational dataset. When this holds with possibly biased measurements of the outcome of interest i…
stat.ME2025
Efficient estimation and data fusion under general semiparametric restrictions on outcome mean functions
Harrison H. Li
We provide a novel characterization of semiparametric efficiency in a generic supervised learning setting where the outcome mean function -- defined as the conditional expectation…
stat.ME2024
Setting the duration of online A/B experiments
Harrison H. Li, Chaoyu Yu
In designing an online A/B experiment, it is crucial to select a sample size and duration that ensure the resulting confidence interval (CI) for the treatment effect is the right w…