Time-Dependent Cross-Ratio Estimation

• Activity Number: 51
• Type: Invited
• Date/Time: Sunday, August 1, 2010 : 4:00 PM to 5:50 PM
• Sponsor: IMS
• Author(s): Bin Nan*+ and Tianle Hu and Xihong Lin and James Robins
• Companies: University of Michigan and University of Michigan and Harvard School of Public Health and Harvard School of Public Health
• Keywords: Bivariate survival time ; Empirical process theory ; Local dependency measure ; Pseudo-partial likelihood

Abstract

In the analysis of bivariate correlated failure time data, it is important to measure the strength of association among the correlated failure times. One commonly used such measure is the cross-ratio. Motivated by the Cox's partial likelihood idea, we propose a novel parametric estimator for the cross-ratio as a continuous function of both components of the bivariate survival times. We show that the proposed parameter estimator is consistent and asymptotically normal. The performance of the proposed technique in finite samples is examined using simulation studies. In addition, the proposed method is applied to the Australian twin data for the estimation of dependence of age at appendectomy between monozygotic twin pairs as well as dizygotic twin pairs.