4 citations · 4 across the 3 of their papers we have counts for
8 papers
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…
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…
Missing at Random or Not: A Semiparametric Testing Approach
Rui Duan, C. Jason Liang, Pamela Shaw +2
Practical problems with missing data are common, and statistical methods have been developed concerning the validity and/or efficiency of statistical procedures. On a central focus…
Novel Non-Negative Variance Estimator for (Modified) Within-Cluster Resampling
Daniel Xu, Pamela Shaw, Ian Barnett
This article proposes a novel variance estimator for within-cluster resampling (WCR) and modified within-cluster resampling (MWCR) - two existing methods for analyzing longitudinal…
Combining multiple imputation with raking of weights: An efficient and robust approach in the setting of nearly-true models
Kyunghee Han, Pamela A. Shaw, Thomas Lumley
Multiple imputation provides us with efficient estimators in model-based methods for handling missing data under the true model. It is also well-understood that design-based estima…
Regression to the Mean's Impact on the Synthetic Control Method: Bias and Sensitivity Analysis
Nicholas Illenberger, Dylan S. Small, Pamela A. Shaw
To make informed policy recommendations from observational data, we must be able to discern true treatment effects from random noise and effects due to confounding. Difference-in-D…