English  |  正體中文  |  简体中文  |  Items with full text/Total items : 6507/11669
Visitors : 30786287      Online Users : 279
RC Version 3.2 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Adv. Search
LoginUploadHelpAboutAdminister

Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/14049

Title: Model Selection for Two-sample Problems with Right-censored Data: An Application of Cox Model
Authors: Chen, Chun-Shu;Chang, Yu-Mei
Contributors: 統計資訊研究所
Keywords: Confidence interval;Data perturbation;Generalized degrees of freedom;Information criterion;Kullback-Leibler loss;Median survival time
Date: 2011-06
Issue Date: 2012-09-10T04:39:01Z
Publisher: Elsevier
Abstract: For investigating differences between two treatment groups in medical science, selecting a suitable model to capture the underlying survival function for each group with some covariates is an important issue. Many methods, such as stratified Cox model and unstratified Cox model, have been proposed for investigating the problem. However, different models generally perform differently under different circumstances and none dominates the others. In this article, we focus on two sample problems with right-censored data and propose a model selection criterion based on an approximately unbiased estimator of Kullback–Leibler loss, which accounts for estimation uncertainty in estimated survival functions obtained by various candidate models. The effectiveness of the proposed method is justified by some simulation studies and it also applied to an HIV+ data set for illustration.
Relation: Journal of Statistical Planning and Inference, 141(6): 2120-2127
Appears in Collections:[統計資訊研究所] 期刊論文

Files in This Item:

File SizeFormat
index.html0KbHTML877View/Open


All items in NCUEIR are protected by copyright, with all rights reserved.

 


DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback