6 papers
Marginal generalized raking with parametric working models
Brian D Williamson, Runjia Zou, Thomas Lumley +2
Generalized raking (GR) was originally developed in the survey statistics literature to incorporate auxiliary information in estimation. Recently, it has been used in the biostatis…
Methods to address measurement error in both Outcome and Covariates
Pamela A. Shaw, Bryan E. Shepherd
Biomedical research is increasingly relying on readily available routine data, such as electronic health records. Routinely collected data, as well as datasets from large cohorts,…
De-meaning Simulation Studies
Thomas Lumley, Brian Williamson, Pamela Shaw
In simulation studies evaluating asymptotic approximations it is common practice to report averages and standard deviations over repeated simulations. We argue that quantile-based…
Optimal two-phase sampling designs for generalized raking estimators with multiple parameters of interest
Jasper B. Yang, Bryan E. Shepherd, Thomas Lumley +1
Large observational datasets, including those derived from electronic health records, are a valuable resource for medical research but are often affected by missingness, measuremen…
Assessing treatment effects in observational data with missing confounders: A comparative study of practical doubly-robust and traditional missing data methods
Brian D. Williamson, Chloe Krakauer, Eric Johnson +13
In pharmacoepidemiology, safety and effectiveness are frequently evaluated using readily available administrative and electronic health records data. In these settings, detailed co…
High-dimensional multiple imputation (HDMI) for partially observed confounders including natural language processing-derived auxiliary covariates
Janick Weberpals, Pamela A. Shaw, Kueiyu Joshua Lin +17
Multiple imputation (MI) models can be improved by including auxiliary covariates (AC), but their performance in high-dimensional data is not well understood. We aimed to develop a…