Date of Award
Fall 2021
Document Type
Open Access Thesis
Department
Mathematics
First Advisor
Bo Cai
Abstract
In this paper, we consider the problem of multiple frailty selection for general interval-censored spatial survival data, which often occurs in clinical trials and epidemiological studies. The general interval-censored data is a mixture of left-, right- and interval-censored data. We propose a Bayesian semiparametric approach based on the Cox proportional hazard model, where monotone splines were used for non-parametrical modeling of the cumulative baseline hazards where the variable selection priors were used for frailty selection. A two-stage data augmentation with Poisson latent variables is developed for efficient computation. The approach is evaluated based a simulation study and illustrated using a set of geographically referenced smoking cessation data in Minnesota. The whole procedure is implemented in software R 4.0.4 and WinBUGS.
Rights
© 2021, Wanfang Zhang
Recommended Citation
Zhang, W.(2021). Multiple Frailty Model for Spatially Correlated Interval-Censored. (Master's thesis). Retrieved from https://scholarcommons.sc.edu/etd/6873