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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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 Title & Authors
Analysis of multi-center bladder cancer survival data using variable-selection method of multi-level frailty models
Kim, Bohyeon; Ha, Il Do; Lee, Donghwan;
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 Abstract
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 multi-level 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.
 Keywords
Multi-level frailty models;penalized hierarchical-likelihood;penalized variable selection;
 Language
Korean
 Cited by
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