Title

Trees for correlated survival data by goodness of split, with applications to tooth prognosis

Authors

Authors

J. J. Fan; X. G. Su; R. A. Levine; M. E. Nunn;M. LeBlanc

Comments

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Abbreviated Journal Title

J. Am. Stat. Assoc.

Keywords

classification rule; correlated survival data; regression tree; robust; logrank statistic; survival analysis; tooth loss; FAILURE TIME DATA; CLINICAL-PARAMETERS; REGRESSION-ANALYSIS; RANK; STATISTICS; MODELS; IDENTIFICATION; Statistics & Probability

Abstract

In this article the regression tree method is extended to correlated survival data and applied to the problem of developing objective prognostic classification rules in periodontal research. The robust logrank statistic is used as the splitting statistic to measure the between-node difference in survival, while adjusting for correlation among failure times from the same patient. The partition-based survival function estimator is shown to converge to the true conditional survival function. Tooth loss data from 100 periodontal patients (2,509 teeth) was analyzed using the proposed method. The goal is to assign each tooth to one of the five prognosis categories (good, fair, poor, questionable, or hopeless). After the best-sized tree was identified, an amalgamation procedure was used to form five prognostic groups. The prognostic rules established here may be used by periodontists, general dentists, and insurance companies in devising appropriate treatment plans for periodontal patients.

Journal Title

Journal of the American Statistical Association

Volume

101

Issue/Number

475

Publication Date

1-1-2006

Document Type

Article

Language

English

First Page

959

Last Page

967

WOS Identifier

WOS:000240158700009

ISSN

0162-1459

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