COMPETING RISKS COX PROPORTIONAL HAZARDS MODEL THROUGH CAUSE SPECIFIC AND SUB-DISTRIBUTIONAL HAZARDS: A MODEL COMPARISON
- Department of Epidemiology, The TamilNadu Dr.MGR Medical University, India.
- Cognizant Technology Solutions (Chennai), India.
- Department of Statistics, National Institute for Research in Tuberculosis (ICMR), India.
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Competing risks data emerge when the individuals under study can experience with multiple endpoints, and for each individual the time to failure and the type of failure will be observed. Consequently, the competing risks data is the extension to the ordinary survival time data which only concern with one endpoint. Sometimes the focus is not on the parameter estimates, but moderately on the probability of observing a failure from a specific cause for individuals with specified covariate values. The intention of this paper is to model the cause specific hazard and sub-distribution hazard for endpoint using Cox proportional hazard. This interpretation discusses and distinguishes between the two common types of competing risk analyses and cumulative incidence curves. It is concluded that the cause-specific hazards model is an advantageous approach than the sub-distribution hazards model. The application of the method is illustrated with an open source Bone Marrow Transplant data.
[Valarmathi S, Babu C Lakshmanan, Ponnuraja C (2015); COMPETING RISKS COX PROPORTIONAL HAZARDS MODEL THROUGH CAUSE SPECIFIC AND SUB-DISTRIBUTIONAL HAZARDS: A MODEL COMPARISON Int. J. of Adv. Res. 3 (Jun). ] (ISSN 2320-5407). www.journalijar.com
