Improved AIC selection strategy for survival analysis

doi:10.1016/j.csda.2007.09.003

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	Improved AIC selection strategy for survival analysis
	Liang, Hua 1; Zou, Guohua 1,2
	2008-01-20
发表期刊	COMPUTATIONAL STATISTICS & DATA ANALYSIS
ISSN	0167-9473
卷号	52 期号:5 页码:2538-2548
摘要	In survival analysis, it is of interest to appropriately select significant predictors. In this paper, we extend the AIC(C) selection procedure of Hurvich and Tsai to survival models to improve the traditional AIC for small sample sizes. A theoretical verification under a special case of the exponential distribution is provided. Simulation studies illustrate that the proposed method substantially outperforms its counterpart: AIC, in small samples, and competes it in moderate and large samples. Two real data sets are also analyzed. (c) 2007 Elsevier B.V. All rights reserved.
关键词	AIC BIC Kullback-Leibler information survival analysis
DOI	10.1016/j.csda.2007.09.003
语种	英语
WOS研究方向	Computer Science ; Mathematics
WOS类目	Computer Science, Interdisciplinary Applications ; Statistics & Probability
WOS记录号	WOS:000253178600019
出版者	ELSEVIER SCIENCE BV
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/6989
专题	中国科学院数学与系统科学研究院
通讯作者	Liang, Hua
作者单位	1.Univ Rochester, Med Ctr, Dept Biostat & Comp Biol, Rochester, NY 14642 USA 2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Liang, Hua,Zou, Guohua. Improved AIC selection strategy for survival analysis[J]. COMPUTATIONAL STATISTICS & DATA ANALYSIS,2008,52(5):2538-2548.
APA	Liang, Hua,&Zou, Guohua.(2008).Improved AIC selection strategy for survival analysis.COMPUTATIONAL STATISTICS & DATA ANALYSIS,52(5),2538-2548.
MLA	Liang, Hua,et al."Improved AIC selection strategy for survival analysis".COMPUTATIONAL STATISTICS & DATA ANALYSIS 52.5(2008):2538-2548.