5 papers
History-Aware Conformal Prediction Sets for Censored Time-to-Event Outcomes
Yuyao Wang, Alexander W. Levis, Shu Yang +1
Existing conformal prediction methods for time-to-event outcomes leverage only baseline covariates, producing prediction intervals that are insufficiently informative to facilitate…
Robust Causal Inference for EHR-based Studies of Point Exposures with Missingness in Eligibility Criteria
Luke Benz, Rajarshi Mukherjee, Rui Wang +6
Missingness in variables that define study eligibility criteria is a seldom addressed challenge in electronic health record (EHR)-based settings. It is typically the case that pati…
A Statistical Framework for Understanding Causal Effects that Vary by Treatment Initiation Time in EHR-based Studies
Luke Benz, Rajarshi Mukherjee, Rui Wang +6
Standard practice in electronic health record (EHR)-based studies evaluating the comparative effectiveness of bariatric surgery relative to no surgery is to estimate and report a c…
Comparing Causal Inference Methods for Point Exposures with Missing Confounders: A Simulation Study
Luke Benz, Alexander Levis, Sebastien Haneuse
Causal inference methods based on electronic health record (EHR) databases must simultaneously handle confounding and missing data. Vast scholarship exists aimed at addressing thes…
Causal Quantile Treatment Effects with missing data by double-sampling
Shuo Sun, Sebastien Haneuse, Alexander W. Levis +5
Causal weighted quantile treatment effects (WQTE) are a useful complement to standard causal contrasts that focus on the mean when interest lies at the tails of the counterfactual…