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    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/118095

    题名: Varying coefficient transformation cure models for failure time data
    作者: Chen, Man-Hua;Tong, Xingwei
    关键词: Cure model;Maximum likelihood estimation;Regression analysis;Spline smoothing
    日期: 2019-10-09
    上传时间: 2020-02-15 12:10:32 (UTC+8)
    摘要: This article discusses regression analysis of right-censored failure time data where there may exist a cured subgroup, and also covariate effects may be varying with time, a phenomena that often occurs in many medical studies. To address the problem, we discuss a class of varying coefficient transformation models along with a logistic model for the cured subgroup. For inference, a sieve maximum likelihood approach is developed with the use of spline functions, and the asymptotic properties of the proposed estimators are established. The proposed method can be easily implemented, and the conducted simulation study suggests that the proposed method works well in practical situations. An illustrative example is provided.
    關聯: Lifetime Data Analysis (27 pages)
    显示于类别:[統計學系暨研究所] 期刊論文





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