Data Fusion for Errors-in-Variables
We study errors-in-variables problems in which a target study contains only a single error-prone surrogate of an unobserved exposure, while an external source study provides repeated surrogate measurements from a different population.
By Huali Zhao, Molei Liu, Tianying WangarXiv - stat.ML
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Originally published by arXiv - stat.ML on Oct 7, 2026.
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