A leave-one-out cross-validation SAS macro for the identification of markers associated with survival

被引：44
|
作者：
Rushing, Christel [1 ,2 ]
Bulusu, Anuradha [1 ,2 ]
Hurwitz, Herbert I. [3 ]
Nixon, Andrew B. [3 ]
Pang, Herbert [1 ,2 ,4 ]
机构：
[1] Duke Univ, Sch Med, Dept Biostat & Bioinformat, Durham, NC USA
[2] Duke Univ, Sch Med, Duke Canc Biostat, Durham, NC USA
[3] Duke Univ, Sch Med, Dept Med, Durham, NC 27706 USA
[4] Li Ka Shing Fac Med, Sch Publ Hlth, Pok Fu Lam, Hong Kong, Peoples R China
来源：
COMPUTERS IN BIOLOGY AND MEDICINE | 2015年 / 57卷
基金：
美国国家卫生研究院;
关键词：
Clinical trials; Cross-validation; Prognostic markers; SAS macro; Score selection; Survival analysis;
D O I：
10.1016/j.compbiomed.2014.11.015
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
A proper internal validation is necessary for the development of a reliable and reproducible prognostic model for external validation. Variable selection is an important step for building prognostic models. However, not many existing approaches couple the ability to specify the number of covariates in the model with a cross-validation algorithm. We describe a user-friendly SAS macro that implements a score selection method and a leave-one-out cross-validation approach. We discuss the method and applications behind this algorithm, as well as details of the SAS macro. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码：123 / 129
页数：7
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