19 citations · 38 across the 5 of their papers we have counts for
5 papers
A penalized likelihood approach for efficiently estimating a partially linear additive transformation model with current status data
Yan Liu, Minggen Lu, Christopher S. McMahan
Current status data are commonly encountered in medical and epidemiological studies in which the failure time for study units is the outcome variable of interest. Data of this form…
A proportional hazards model for interval-censored data subject to instantaneous failures
Prabhashi W. Withana Gamage, Monica Chaudari, Christopher S. McMahan +1
The proportional hazards (PH) model is arguably one of the most popular models used to analyze time to event data arising from clinical trials and longitudinal studies, among many…
A Large Scale Spatio-temporal Binomial Regression Model for Estimating Seroprevalence Trends
Stella Watson Self, Christopher McMahan, D. Andrew Brown +3
This paper develops a large-scale Bayesian spatio-temporal binomial regression model for the purpose of investigating regional trends in antibody prevalence to Borrelia burgdorferi…
Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging
D. Andrew Brown, Christopher S. McMahan, Russell T. Shinohara +1
Alzheimer's disease is a neurodegenerative condition that accelerates cognitive decline relative to normal aging. It is of critical scientific importance to gain a better understan…
Sampling strategies for fast updating of Gaussian Markov random fields
D. Andrew Brown, Christopher S. McMahan, Stella Watson Self
Gaussian Markov random fields (GMRFs) are popular for modeling dependence in large areal datasets due to their ease of interpretation and computational convenience afforded by the…