8 papers
Toward Joint Prediction of a Longitudinal Marker and a Terminal Event: A bivariate discrete-time framework
Stephanie Armbruster, Daniel Kramer, Rui Duan +3
Sudden cardiac death (SCD) is a leading cause of death in the U.S. Patients at elevated risk of SCD are primarily treated with an implantable cardioverter-defibrillator (ICD), whic…
On the Asymptotic Inadmissibility of Double Machine Learning Estimators Under Structure-Agnostic Models
Lin Liu, Rajarshi Mukherjee, James M Robins
Structure-agnostic (SA) models introduced by Balakrishnan et al. (2026) aim to reflect the general lack of knowledge of structural assumptions on data-generating laws such as smoot…
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…
Asymptotic Inference for Constrained Regression
Madhav Sankaranarayanan, Yana Hrytsenko, Jerome I. Rotter +2
We consider statistical inference in high-dimensional regression problems under affine constraints on the parameter space. The theoretical study of this is motivated by the study o…
Sensitivity analysis for nonignorable missing values in blended analysis framework: a study on the effect of bariatric surgery via electronic health records
Jungwun Lee, Sebastien Haneuse, Rajarshi Mukherjee +1
This paper establishes a series of sensitivity analyses to investigate the impact of missing values in the electronic health records (EHR) that are possibly missing not at random (…