8 citations · 12 across the 7 of their papers we have counts for
5 papers · 1 filter
A Doubly Robust Framework for Addressing Outcome-Dependent Selection Bias in Multi-Cohort EHR Studies
Ritoban Kundu, Xu Shi, Michael Kleinsasser +3
Selection bias can hinder accurate estimation of association parameters in binary disease risk models using non-probability samples like electronic health records (EHRs). The issue…
Generating Synthetic Electronic Health Record Data: a Methodological Scoping Review with Benchmarking on Phenotype Data and Open-Source Software
Xingran Chen, Zhenke Wu, Xu Shi +2
We conduct a scoping review of existing approaches for synthetic EHR data generation, and benchmark major methods with proposed open-source software to offer recommendations for pr…
A new statistical approach for joint modeling of longitudinal outcomes measured in electronic health records with clinically informative presence and observation processes
Jiacong Du, Xu Shi, Bhramar Mukherjee
Biobanks with genetics-linked electronic health records (EHR) have opened up opportunities to study associations between genetic, social, or environmental factors and longitudinal…
What's the Weight? Estimating Controlled Outcome Differences in Complex Surveys for Health Disparities Research
Stephen Salerno, Emily K. Roberts, Belinda L. Needham +4
In this work, we are motivated by the problem of estimating racial disparities in health outcomes, specifically the average controlled difference (ACD) in telomere length between B…
Doubly robust causal inference through penalized bias-reduced estimation: combining non-probability samples with designed surveys
Jiacong Du, Xu Shi, Donglin Zeng +1
Causal inference on the average treatment effect (ATE) using non-probability samples, such as electronic health records (EHR), faces challenges from sample selection bias and high-…