Empirical Bayes rebiasing learns the bias distribution from paired noisy estimates to produce shorter calibrated intervals than full debiasing while maintaining coverage.
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Calibration experiments allow empirical Bayes to learn observational bias distributions, enabling consistent causal effect estimation from observational studies.
A review organizes externally controlled trial methodology through causal estimands and identifiability assumptions for single-arm and hybrid designs with borrowing strategies.
citing papers explorer
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Empirical Bayes Rebiasing
Empirical Bayes rebiasing learns the bias distribution from paired noisy estimates to produce shorter calibrated intervals than full debiasing while maintaining coverage.
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The Illusion of Learning from Observational Data: An Empirical Bayes Perspective
Calibration experiments allow empirical Bayes to learn observational bias distributions, enabling consistent causal effect estimation from observational studies.
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Externally Controlled Trials: A Review of Design and Borrowing Through a Causal Lens
A review organizes externally controlled trial methodology through causal estimands and identifiability assumptions for single-arm and hybrid designs with borrowing strategies.