Post-hoc calibration of miscalibrated black-box predictions on a labeled sample improves efficiency of prediction-powered inference for semisupervised mean estimation.
Conditional influence functions.arXiv preprint arXiv:2412.18080
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A semiparametric method using conditional influence functions and local linear regression is proposed to estimate CATE functions in the target population from nested trial data.
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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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Generalizing conditional average treatment effects from nested randomized trials to all trial-eligible individuals
A semiparametric method using conditional influence functions and local linear regression is proposed to estimate CATE functions in the target population from nested trial data.