Joint modeling of longitudinal proportional measurements and survival time with a cure fraction

被引：0
作者：
Hui Song
YingWei Peng
DongSheng Tu
机构：
[1] Dalian University of Technology,School of Mathematical Sciences
[2] Queen’s University,Departments of Public Health Sciences & Mathematics and Statistics
[3] Queen’s University,Canadian Cancer Trials Group
来源：
Science China Mathematics | 2016年 / 59卷
关键词：
cure fraction; joint model; Laplace approximation; proportional data; simplex distribution; survival times; 62N86; 62G05; 62P10;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In cancer clinical trials and other medical studies, both longitudinal measurements and data on a time to an event (survival time) are often collected from the same patients. Joint analyses of these data would improve the efficiency of the statistical inferences. We propose a new joint model for the longitudinal proportional measurements which are restricted in a finite interval and survival times with a potential cure fraction. A penalized joint likelihood is derived based on the Laplace approximation and a semiparametric procedure based on this likelihood is developed to estimate the parameters in the joint model. A simulation study is performed to evaluate the statistical properties of the proposed procedures. The proposed model is applied to data from a clinical trial on early breast cancer.
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收藏
页码：2427 / 2442
页数：15
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