Measures of explained variation for a regression model used in survival analysis

被引：3
作者：
Akazawa K. [1 ]
机构：
[1] Kyushu University, Faculty of Medicine, Department of Medical Informatics, Higashi-ku
来源：
Journal of Medical Systems | 1997年 / 21卷 / 4期
关键词：
Clinical trial; Explained variation; Regression model; Survival analysis;
D O I：
10.1023/A:1022884504683
中图分类号：
学科分类号：
摘要：
This paper describes a measure of explained variation (MEV) of survival times for a given regression model used in survival analysis. It quantifies the predictive power of a set of prognostic factors in the model, and therefore provides useful information for more precise prediction of patient prognosis, and for designing randomized clinical trials with the capability of determining treatment effects. The MEV defined in this article is asymptotically derived from the squared product-moment correlation; it can be interpreted as an adaptation of the multiple correlation coefficient for the normal linear model to the Survival time regression model. Monte-Carlo simulations are performed to investigate the statistical behavior of the proposed MEV. The MEV is applied to estimate the predictive power of several sets of prognostic factors for gastric cancer in Japan using data from a large clinical trial.
引用
收藏
页码：229 / 238
页数：9
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