M.S. (Master of Science)
Department of Statistics
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.
Liu, Yanjun, "Bayesian semiparametric accelerated hazards model for arbitrarily censored spatial survival data" (2017). Graduate Research Theses & Dissertations. 1612.
Northern Illinois University
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