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.
Biometrics , volume=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
stat.ME 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
CAFE assesses the fit of observational CATE estimates by partitioning RCT data via propensity scores and comparing to experimental group averages, with theory and extensions for confounders.
citing papers explorer
-
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.
-
Assessing Estimate of CATE from Observational Data via an RCT Study
CAFE assesses the fit of observational CATE estimates by partitioning RCT data via propensity scores and comparing to experimental group averages, with theory and extensions for confounders.