Long-Term Survival for Competing Risk Data with Masked Causes

• Activity Number: 130
• Type: Contributed
• Date/Time: Monday, July 30, 2012 : 8:30 AM to 10:20 AM
• Sponsor: Biometrics Section
• Author(s): Ronny Westerman*+
• Companies: University of Marburg
• Keywords: comepting risks ; masked causes ; long-term survival ; stroke

Abstract

Competing Risks Models have a various field of application in medical and public health studies. A challenging clue for applying cause-specific survival models yield on the problem of missing and misclassification in cause of death. The masked cause of death is related to incomplete or only partial identifiable in formation of death certificates. Different Bayesian approaches e.g. the mixture cure model (Basu and Tiwari, 2010) are proposed to account for that problem. Another question is related to adequate estimates for long-term survival in respect to the limitation of lifetime among all risks. As a new parametric distribution the long-term exponential distribution (LEG) introduced by Roman et al. 2012 can be considered. The main purpose of this work is to compare the LEG with alternative parametric versions like Weibull distribution, or the simple Exponential distribution for long-ter