5 papers
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. It is typically the case that pati…
Self-Consistent Equation-guided Neural Networks for Censored Time-to-Event Data
Sehwan Kim, Rui Wang, Wenbin Lu
In survival analysis, estimating the conditional survival function given predictors is often of interest. There is a growing trend in the development of deep learning methods for a…
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…
Nested Instrumental Variables Analysis: Switcher Average Treatment Effect, Identification, Efficient Estimation and Generalizability
Rui Wang, Ying-Qi Zhao, Oliver Dukes +1
Instrumental variables (IVs) are widely used to estimate causal effects from non-randomized data. A canonical example is a randomized trial with noncompliance, in which the randomi…