Develops a multiply robust iDID estimator for optimal policies in recurrent events with terminal competing risk, with simulation results and application to Medicare Type 2 diabetes data.
Prediction-powered generalization of causal inferences.arXiv preprint arXiv:2406.02873
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Post-hoc calibration of miscalibrated black-box predictions on a labeled sample improves efficiency of prediction-powered inference for semisupervised mean estimation.
Tutorial on a statistical roadmap and R packages for selective borrowing in hybrid controlled trials, demonstrated on synthetic lung cancer data.
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Optimal Treatment Policy Estimation for Recurrent Events with a Competing Terminal Event: An Instrumented Difference-in-Differences Approach
Develops a multiply robust iDID estimator for optimal policies in recurrent events with terminal competing risk, with simulation results and application to Medicare Type 2 diabetes 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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Robust Estimation and Inference with Selective Borrowing in Hybrid Controlled Trials: A Tutorial with SelectiveIntegrative and intFRT
Tutorial on a statistical roadmap and R packages for selective borrowing in hybrid controlled trials, demonstrated on synthetic lung cancer data.