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Abstract Details

Activity Number: 130
Type: Contributed
Date/Time: Monday, July 30, 2012 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #305989
Title: A Generalization of the Odd Weibull Distribution for Modeling Cumulative Incidence Functions in Competing Risk Analysis
Author(s): Kahadawala Cooray*+
Companies: Central Michigan University
Address: 1777 Rose Marie Lane, Mount Pleasant, MI, 48858-9573, United States
Keywords: cause-specific hazard ; competing risks ; cumulative incidence ; odd Weibull ; Weibull

In competing risk analysis, the event of interest and the competing event may not follow a common hazard shape. Therefore, it is natural to consider a more flexible parametric model that can accommodate a wide variety of hazard shapes to properly capture the various shapes of the cumulative incidence functions. In this regard, we consider a generalization of the odd Weibull distribution which can accommodate seven different hazard shapes and a wide variety of density shapes for modeling the cumulative incidence function in the presence of censored data. Parametric inferences for the cumulative incidence functions under the maximum likelihood method are performed using cause-specific hazard approach and direct parametric modeling (Jeong and Fine, 2006). Finally the advantages of the proposed model are demonstrated and compared with its nonparametric counterpart as well as existing parametric models by analyzing the follicular cell lymphoma dataset.

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