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Data Fusion for Errors-in-Variables

Zhao, Huali et al.
arXiv (All) · Papers
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machine-learningmethodologystatistics-theory
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. The measurement error distribution is allowed to depend on the ob
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