5 papers
Characterizing Survivor Principal Strata Over Time: Identification, Efficient Estimation, and Sensitivity Analysis
Keith Barnatchez, Willow Butler, Julia A. Geller +1
Longitudinal studies with functional outcomes subject to truncation-by-death frequently report time-indexed survivor average causal effect estimates, defined among individuals who…
Causal Inference with Multiple Misclassified Exposures: A Control Variate-Adjusted Calibration Weighting Approach
Nandini Murali, Keith Barnatchez, Jordana E. Hoppe +3
Exposure misclassification is a common issue prevalent in studies of respiratory infections in cystic fibrosis. Throat swabs are frequently used in place of expectorated or induced…
Debiased Machine Learning for Conformal Prediction of Counterfactual Outcomes Under Runtime Confounding
Keith Barnatchez, Kevin P. Josey, Rachel C. Nethery +1
Data-driven decision making frequently relies on predicting counterfactual outcomes. In practice, researchers commonly train counterfactual prediction models on a source dataset to…
Efficient Estimation of Causal Effects Under Two-Phase Sampling with Error-Prone Outcome and Treatment Measurements
Keith Barnatchez, Kevin P. Josey, Nima S. Hejazi +3
Measurement error is a common challenge for causal inference studies using electronic health record (EHR) data, where clinical outcomes and treatments are frequently mismeasured. R…
Flexible and Efficient Estimation of Causal Effects with Error-Prone Exposures: A Control Variates Approach for Measurement Error
Keith Barnatchez, Rachel Nethery, Bryan E. Shepherd +2
Exposure measurement error is a ubiquitous but often overlooked challenge in causal inference with observational data. Existing methods accounting for exposure measurement error la…