collaborators

6 papers

stat.ME2026

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…

stat.ME2026

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…

stat.ME2026

Addressing errors in multiple variables using generalized raking and cumulative probability models

Eric S. Kawaguchi, Chun Li, Frank E. Harrell +3

Routinely collected data, such as electronic health record (EHR) data, are frequently used for biomedical research, but these data are prone to errors, which can bias study finding…

stat.ME2026

Generalized raking and stabilized weights for regression modeling in two-phase samples

Tong Chen, Joshua Slone, Gustavo Amorim +3

In regression models fitted to data from complex survey designs, sampling weights often incorporate non-essential variation, inflating variance estimates. Stabilized weights mitiga…

stat.ME2026

Design-Based Inference for the AUC with Complex Survey Data

Amaia Iparragirre, Thomas Lumley, Irantzu Barrio

Complex survey data are usually collected following complex sampling designs. Accounting for the sampling design is essential to obtain unbiased estimates and valid inferences when…

stat.ME2026

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…