American Statistical Association
New York City
Metropolitan Area Chapter

Memorial Sloan-Kettering Cancer Center
Biostatistics Seminar



Sanjib Basu
Division of Statistics
Northern Illinois University

A UNIFIED COMPETING RISKS CURE RATE MODEL
WITH APPLICATION TO CANCER SURVIVAL DATA

A competing risks framework refers to multiple risks acting simultaneously on a subject. A cure rate postulates a fraction of the subjects to be cured or failure-free, and can be formulated as a mixture model, or alternatively by a bounded cumulative hazard model. We develop models that unify the competing risks and cure rate approaches. The identifiability of these unified models is studied in detail. We describe Bayesian analysis of these models, and discuss conceptual, methodological, and computational issues related to model fitting and model selection. We describe detailed applications in survival data from breast cancer patients in the Surveillance, Epidemiology, and End Results (SEER) program of the National Cancer Institute (NCI) of the United States.


Date: Wednesday, April 10, 2013
Time: 11:00 A.M. - 12:00 P.M.
Location: Memorial Sloan-Kettering Cancer Center
Department of Epidemiology and Biostatistics
307 East 63rd Street
(between First and Second Avenues)
3rd Floor Conference Room
New York, New York
Note: To gain access to the building, please follow the directions by the telephone in the foyer.

RESERVATIONS ARE NOT REQUIRED


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