activity
20182020
most citedTwo-phase analysis and study design for survival models with error-prone exposures

4 citations · 4 across the 2 of their papers we have counts for

collaborators

5 papers

stat.ME2020

Improved Generalized Raking Estimators to Address Dependent Covariate and Failure-Time Outcome Error

Eric J. Oh, Bryan E. Shepherd, Thomas Lumley +1

Biomedical studies that use electronic health records (EHR) data for inference are often subject to bias due to measurement error. The measurement error present in EHR data is typi…

stat.ME20204 cited

Two-phase analysis and study design for survival models with error-prone exposures

Kyunghee Han, Thomas Lumley, Bryan E. Shepherd +1

Increasingly, medical research is dependent on data collected for non-research purposes, such as electronic health records data (EHR). EHR data and other large databases can be pro…

stat.ME2019

Raking and Regression Calibration: Methods to Address Bias from Correlated Covariate and Time-to-Event Error

Eric J. Oh, Bryan E. Shepherd, Thomas Lumley +1

Medical studies that depend on electronic health records (EHR) data are often subject to measurement error, as the data are not collected to support research questions under study.…

stat.ME2018

Regression calibration to correct correlated errors in outcome and exposure

Pamela Shaw, Jiwei He, Bryan Shepherd

Measurement error arises through a variety of mechanisms. A rich literature exists on the bias introduced by covariate measurement error and on methods of analysis to address this…

stat.AP2018

Post-randomization Biomarker Effect Modification in an HIV Vaccine Clinical Trial

Peter B. Gilbert, Bryan S. Blette, Bryan E. Shepherd +1

While the HVTN 505 trial showed no overall efficacy of the tested vaccine to prevent HIV infection over placebo, previous studies, biological theories, and the finding that immune…