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Activity Number: 95
Type: Topic Contributed
Date/Time: Monday, July 30, 2007 : 8:30 AM to 10:20 AM
Sponsor: ENAR
Abstract - #308414
Title: General Transformation Models for Joint Analysis of Recurrent Events and Terminal Event
Author(s): Donglin Zeng*+ and Danyu Lin
Companies: The University of North Carolina at Chapel Hill and The University of North Carolina at Chapel Hill
Address: Department of Biostatistics, Chapel Hill, NC, 27599-7420,
Keywords: Recurrent event ; Terminal event ; Transformation model ; Joint model ; Informative censoring
Abstract:

We propose a class of transformation models with random effects for joint modeling recurrent events and terminal event. The class of transformation models include both the proportional hazards model and the proportional odds model as special cases. The nonparametric maximum likelihood estimation method is used to derive the estimators, which are then shown to be consistent, asymptotically normal and asymptotically efficient. A simple algorithm is proposed to calculate the estimators. Simulation studies are conducted to examine the small-sample performance of the proposed method. The method is further applied to a real dataset.

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Revised September, 2007