Statistics and Probability Commons^™

Temporal Dynamics Of Neural Activity In The Olfactory Receptor Neurons During Odor Exposure, Danni Liu, Jun Xia

Georgia State Undergraduate Research Conference

No abstract provided.

Additive And Multiplicative Hazards Modeling For Recurrent Event Data Analysis, Hyun J. Lim, Xu Zhang

Mathematics and Statistics Faculty Publications

Background: Sequentially ordered multivariate failure time or recurrent event duration data are commonly observed in biomedical longitudinal studies. In general, standard hazard regression methods cannot be applied because of correlation between recurrent failure times within a subject and induced dependent censoring. Multiplicative and additive hazards models provide the two principal frameworks for studying the association between risk factors and recurrent event durations for the analysis of multivariate failure time data.

Methods: Using emergency department visits data, we illustrated and compared the additive and multiplicative hazards models for analysis of recurrent event durations under (i) a varying baseline with a common …

Methods Of Competing Risks Analysis Of End-Stage Renal Disease And Mortality Among People With Diabetes, Hyun J. Lim, Xu Zhang, Roland Dyck, Nathaniel Osgood

Mathematics and Statistics Faculty Publications

Background: When a patient experiences an event other than the one of interest in the study, usually the probability of experiencing the event of interest is altered. By contrast, disease-free survival time analysis by standard methods, such as the Kaplan-Meier method and the standard Cox model, does not distinguish different causes in the presence of competing risks. Alternative approaches use the cumulative incidence estimator by the Cox models on cause-specific and on subdistribution hazards models. We applied cause-specific and subdistribution hazards models to a diabetes dataset with two competing risks (end-stage renal disease (ESRD) or death without ESRD) to measure …

Comparing Distribution Functions Via Empirical Likelihood, Yichuan Zhao, Ian W. Mckeague

Mathematics and Statistics Faculty Publications

This paper develops empirical likelihood based simultaneous confidence bands for differences and ratios of two distribution functions from independent samples of right-censored survival data. The proposed confidence bands provide a flexible way of comparing treatments in biomedical settings, and bring empirical likelihood methods to bear on important target functions for which only Wald-type confidence bands have been available in the literature. The approach is illustrated with a real data example.