A new James-Stein estimator integrates coarsened external data to improve fine subgroup CATE estimation in RCTs and shows uniform dominance over internal-data-only OLS under mild conditions.
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The authors develop and benchmark inference methods for win statistics in cluster-randomized trials with composite endpoints, filling a gap in handling within-cluster dependence.
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Data Integration for Estimating Subgroup-Specific Conditional Average Treatment Effects (CATEs) Using Coarsened External Information in Randomized Trials
A new James-Stein estimator integrates coarsened external data to improve fine subgroup CATE estimation in RCTs and shows uniform dominance over internal-data-only OLS under mild conditions.
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Statistical inference with win statistics in cluster-randomized trials with composite outcomes
The authors develop and benchmark inference methods for win statistics in cluster-randomized trials with composite endpoints, filling a gap in handling within-cluster dependence.