A new upper bound is derived for the worst-case effect of selection bias on medical prediction model performance under partial observation of the selection process and target data.
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Persistent non-response bias in sample-matched 2024 polls is quantified at ρ=-0.0030 for Trump voters, and a historical-data-informed correction estimator reduces RMSE from 0.13 to 0.05.
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A Practical Upper Bound on Selection Bias Effects in Medical Prediction Models
A new upper bound is derived for the worst-case effect of selection bias on medical prediction model performance under partial observation of the selection process and target data.