Integrating Heterogeneous Information in Randomized Experiments: A Unified Calibration Framework

This paper proposes a unified calibration framework that integrates heterogeneous internal and auxiliary information into randomized experiments under covariate-adaptive randomization via convex optimization, ensuring asymptotic validity and a no-harm efficiency guarantee while accommodating scenarios with growing numbers of strata and information sources.

Wei Ma, Zeqi Wu, Zheng Zhang2026-03-10🔢 math