Publication Date
2017
Document Type
Dissertation/Thesis
First Advisor
Zhou, Haiming
Degree Name
M.S. (Master of Science)
Legacy Department
Department of Statistics
LCSH
Statistics
Abstract
To analyze spatially correlated time-to-event data, PH model is the current most commonly used semiparametric survival model. This paper extends Zhou and Hanson[(2017), 'A unified framework for fitting Bayesian semiparametric models to arbitrarily censored survival data, including spatially referenced data', Journal of the American Statistics Association, in press]'s framework which incorporates PH, AFT, and PO models by adding another competing model, the AH model, and updating their R package spBayesSurv. By using the survregbayes function in this R package, users can easily t and compare PH, PO, AFT, and AH model. Having another easy-to-fit model available for comparison is meaningful, especially when we have data that we suspect a lag period existing before a treatment becomes fully effective.
Recommended Citation
Liu, Yanjun, "Bayesian semiparametric accelerated hazards model for arbitrarily censored spatial survival data" (2017). Graduate Research Theses & Dissertations. 1612.
https://huskiecommons.lib.niu.edu/allgraduate-thesesdissertations/1612
Extent
30 pages
Language
eng
Publisher
Northern Illinois University
Rights Statement
In Copyright
Rights Statement 2
NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.
Media Type
Text
Comments
Advisors: Haiming Zhou.||Committee members: Duchwan Ryu; Chaoxiong (Michelle) Xia.||Includes illustrations.||Includes bibliographical references.