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作 者:邓文丽[1] 吴子星 蔡明[2] DENG Wenli;WU Zixing;CAI Ming(School of Mataematatics and Information Science,Jiangxi Normal University,Nanchang,330022,China;Library,Jiangxi Normal University,Nanchang,330022,China)
机构地区:[1]江西师范大学数学与信息科学学院,南昌330022 [2]江西师范大学图书馆,南昌330022
出 处:《应用概率统计》2018年第5期492-500,共9页Chinese Journal of Applied Probability and Statistics
基 金:国家自然科学基金项目(批准号:71001046;11171112;11101114;11201190)资助
摘 要:在临床数据的收集中,由于竞争性风险或者病人的退出可能导致数据删失.删失数据的统计分析大多是基于独立删失的假定进行的.而实际情况中,数据的删失往往是非独立的,即删失变量和失效时间变量是相关的.相依删失使得原本复杂的删失数据处理变得更加困难.在本文中,假定删失变量和失效时间变量的联合分布可以用它们边际分布的连接函数函数表示,在给定连接函数下,得到了比例风险模型的极大似然估计.模拟计算显示,如果删失假定成立,本文所采用方法比独立删失假定下的估计方法更准确.In collecting clinical data,data would be censored due to competing risks or patient withdrawal.The statistical inference for censoring data is always based on the assumption that the failure time and censoring time is independent.But in practice the failure time and censoring time-are often dependent.Dependent censoring make the job to deal with censoring data more complicated.In this paper,we assume that the joint distribution of the failure time variable and censoring time variable is a function of their marginal distributions.This function is called a copula.Under prespecified copulas,the maximum likelihood estimators for cox proportional hazards models are worked out.Statistical analysis results are carried by simulations.When dependent.censoring happens,the proposed method will do better than the traditional method used in independent situations.Simulation results show that the proposed method can get efficient estimations.
分 类 号:O212.1[理学—概率论与数理统计]
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