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Analysis of multi-center bladder cancer survival data using variable-selection method of multi-level frailty models
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다수준 프레일티모형 변수선택법을 이용한다기관 방광암 생존자료분석

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Type
Academic journal
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Journal
The Korean Data and Information Science Society Journal of the Korean Data And Information Science Society Vol.27 No.2 KCI Excellent Accredited Journal
Published
2016.4
Pages
499 - 510 (12page)

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Analysis of multi-center bladder cancer survival data using variable-selection method of multi-level frailty models
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It is very important to select relevant variables in regression models for survival analysis. In this paper, we introduce a penalized variable-selection procedure in multilevel frailty models based on the "frailtyHL" R package (Ha et al., 2012). Here, the estimation procedure of models is based on the penalized hierarchical likelihood, and three penalty functions (LASSO, SCAD and HL) are considered. The proposed methods are illustrated with multi-country/multi-center bladder cancer survival data from the EORTC in Belgium. We compare the results of three variable-selection methods and discuss their advantages and disadvantages. In particular, the results of data analysis showed that the SCAD and HL methods select well important variables than in the LASSO method.
#다수준 프레일티 모형 #벌점화 다단계 가능도 #Multi-level frailty models #벌점화 변수선택 #penalized hierarchical-likelihood #penalized vari-able selection

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