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Model-assisted estimation with a training subsample: a two-phase sampling approach with design-based variance estimation
When a flexible prediction model is fitted on a training subsample drawn from a probability sample, the model-assisted estimator actually reported arises from one realized partition, yet existing theory quantifies uncertainty only for partition-averaged, cross-fitted, or symmetrized versions of it.
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