EcoSta 2018: Registration
View Submission - EcoSta2018
Title: Bayesian cure-rate survival modeling with spatially structured censoring Authors:  Andrew Lawson - Medical University of South Carolina (United States) [presenting]
Georgiana Onicescu - University of Western Michigan (United States)
Abstract: Spatial geo-referencing of survival models is now established and various different approaches are found. Usually the rate parameter of a survival distribution is defined to have such structure. However the censoring mechanism in survival studies would also display important spatial structure and require sensitive modeling. We examine a Bayesian cure rate model which also includes spatial referencing of the censoring mechanism. An application is made to the analysis of prostate cancer from the SEER registry in Louisiana USA.