Post-hoc calibration of miscalibrated black-box predictions on a labeled sample improves efficiency of prediction-powered inference for semisupervised mean estimation.
Robust estimation and inference in hybrid controlled trials for binary outcomes: A case study on non-small cell lung cancer.arXiv preprint arXiv:2505.00217
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Integration of RCTs and real-world data through explicit causal frameworks can yield evidence that is internally credible and externally relevant for individualized treatment decisions.
A review organizes externally controlled trial methodology through causal estimands and identifiability assumptions for single-arm and hybrid designs with borrowing strategies.
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Calibeating Prediction-Powered Inference
Post-hoc calibration of miscalibrated black-box predictions on a labeled sample improves efficiency of prediction-powered inference for semisupervised mean estimation.
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Integration of RCTs and real-world data through explicit causal frameworks can yield evidence that is internally credible and externally relevant for individualized treatment decisions.
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