JSM 2004 - Toronto

Abstract #301970

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Activity Number: 303
Type: Contributed
Date/Time: Wednesday, August 11, 2004 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Computing
Abstract - #301970
Title: Relative Risk Survival Trees with Time-dependent Covariates Using TARGET
Author(s): Guangzhe Fan*+ and J. Brian Gray
Companies: University of Alabama and University of Alabama
Address: 1120 8th St., Tuscaloosa, AL, 35401,
Keywords: genetic algorithm ; counting process ; changepoint ; stochastic search ; maximum likelihood
Abstract:

We propose a new tree-structured model for relative risk (Cox) survival analysis with time-dependent covariates. There are two major contributions in this paper: (1) The TARGET approach, a tree-structured genetic algorithm, is used to construct the survival tree models. It finds trees with smaller size and higher accuracy than traditional greedy search methods. (2) We use a novel way to handle time-dependent covariates based on the likelihood function but without any parametric assumption. Our method can also be easily generalized to the martingale residual survival tree model. Publicly available datasets are used to illustrate the improvement of TARGET methods on traditional models.

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