MEASURES OF EXPLAINED VARIATION FOR SURVIVAL-DATA

被引：118

作者：

KORN, EL

SIMON, R

机构：

[1] Department of Biomathematics, Ucla School of Medicine, Los Angeles, California

[2] Biometric Research Branch, National Cancer Institute, Bethesda, Maryland

[3] Biometric Research Branch, National Cancer Institute, Bethesda, Maryland, 20892, Executive Plaza North

来源：

STATISTICS IN MEDICINE | 1990年 / 9卷 / 05期

关键词：

D O I：

10.1002/sim.4780090503

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

The predictive power of a set of prognostic variables in a survival time model is a concept distinct from the statistical significance of the variables or the adequacy of the model fit. In this paper we discuss the importance of quantifying the predictive power of a prognostic model, and suggest measures of explained variation as a possible quantification. The important features of our approach are that (1) the measures are completely model‐based; (2) a specification of the time range of interest is easily incorporated; and (3) the null models used for comparison are derived as mixtures of the predicted distributions. Copyright © 1990 John Wiley & Sons, Ltd.

引用

页码：487 / 503

页数：17

共 21 条

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