This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 467
Type: Contributed
Date/Time: Wednesday, August 4, 2010 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #308209
Title: Stochastic Frailty Model Induced by Time-Dependent Covariates
Author(s): Lyrica Xiaohong Liu*+
Companies: University of Michigan
Address: SPH II Biostatistics Washington Height, Ann Arbor, MI, 48109,
Keywords: stochastic process ; time dependent covariates ; frailty model
Abstract:

Frailty model is an extension of Cox model when hazards of population demonstrate heterogeneity. Most research treat frailty as some random variable, the underlying assumption is that frailty, though unobserved, is a fixed quantity over time. However, sometimes latent frailty might function as a stochastic process due to the nature of disease incidence, for example, tumor growth, or, due to a dynamic treatment assignment. In both cases, the frailty process changes its distribution characteristics as time goes by. Traditional frailty modeling approach will not be adequate for those types of scenario. In this research, we propose a frailty process model induced by time changing covariates within one subject. We establish the properties of estimates using counting process and Martingale related theories. Finally we apply our method to prostate cancer data from SEER database.


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