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Activity Number: 194
Type: Contributed
Date/Time: Monday, August 10, 2015 : 10:30 AM to 12:20 PM
Sponsor: ENAR
Abstract #316526
Title: Joint Model of Bivariate Survival Times and Longitudinal Data
Author(s): Ke Liu* and Ying Zhang
Companies: and Indiana University
Keywords: Joint Model ; Survival ; Longitudinal
Abstract:

Motivated by a study of Muscular Dystrophy Surveillance Tracking and Research Network (MD STARnet), a joint model of bivariate survival times and longitudinal data is developed. We propose to analyze correlated bivariate survival responses associated with a longitudinal biomarker in the Frequentist paradigm. A Gamma frailty variable is used to account for the correlation between the two correlated survival outcomes in addition to the random variables that account for the correlation between the survival times and longitudinal maker. The EM algorithm is adopted to compute the maximum profile likelihood estimate. The bootstrap method is applied to estimate the standard error of estimated model parameters. The simulation study is conducted to demonstrate the validity of the proposed methodology. Finally the method is applied to the MD STARnet for illustration.

Authors who are presenting talks have a * after their name.

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