Title

Multivariate survival trees: A maximum likelihood approach based on frailty models

Authors

Authors

X. G. Su;J. J. Fan

Comments

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Abbreviated Journal Title

Biometrics

Keywords

Akaike information criterion; frailty models; multivariate survival; times; regression trees; CHRONIC GRANULOMATOUS-DISEASE; FAILURE TIME DATA; INTERFERON-GAMMA; LIFE-TABLES; REGRESSION; HAZARDS; Biology; Mathematical & Computational Biology; Statistics & Probability

Abstract

A method of constructing trees for correlated failure times is put forward. It adopts the backfitting idea of classification and regression trees (CART) (Breiman et al., 1984, in Classification and Regression Trees). The tree method is developed based on the maximized likelihoods associated with the gamma frailty model and standard likelihood-related techniques are incorporated. The proposed method is assessed through simulations conducted under a variety of model configurations and illustrated using the chronic granulomatous disease (CGD) study data.

Journal Title

Biometrics

Volume

60

Issue/Number

1

Publication Date

1-1-2004

Document Type

Article

DOI Link

http://dx.doi.org/10.1111/j.0006-341X.2004.00139.x

Language

English

First Page

93

Last Page

99

WOS Identifier

WOS:000220384400012

ISSN

0006-341X

Recommended Citation

"Multivariate survival trees: A maximum likelihood approach based on frailty models" (2004). Faculty Bibliography 2000s. 4819.
https://stars.library.ucf.edu/facultybib2000/4819