9 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…
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…
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…
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. Patients with incomplete eligibili…
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 (…
Adjusting for Selection Bias Due to Missing Eligibility Criteria in Emulated Target Trials
Luke Benz, Rajarshi Mukherjee, Rui Wang +5
Target trial emulation (TTE) is a popular framework for observational studies based on electronic health records (EHR). A key component of this framework is determining the patient…
Nonsense associations in Markov random fields with pairwise dependence
Sohom Bhattacharya, Rajarshi Mukherjee, Elizabeth Ogburn
Yule (1926) identified the issue of "nonsense correlations" in time series data, where dependence within each of two random vectors causes overdispersion -- i.e. variance inflation…
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…