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Case-cohort设计下多类型事件数据的一类有效估计

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Case-cohort设计下多类型事件数据的一类有效估计 刘君娥1, 周洁21. 淮北师范大学管理学院, 淮北 235000;
2. 首都师范大学数学科学学院, 北京 100048 An Effective Estimating for Case-cohort Designs with Multiple Type Event Data LIU June1, ZHOU Jie21. School of Management, Huaibei Normal University, Huaibei 235000, China;
2. School of Mathematics, Capital Normal University, Beijing 100048, China
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摘要在生物医学统计中,为了节省资源,许多****将生物统计与抽样设计方法有机地结合在一起,于是产生了大量case-cohort设计下的多元失效时间数据.本文主要利用一般的加乘风险回归模型研究case-cohort设计下的多类型事件数据.首先提出了一类有效的加权估计方程,然后给出了参数估计以及所得估计量的渐近性质.数值模拟结果表明,所提出的估计方法更有效.最后,将所提方法进行实例分析.
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收稿日期: 2018-01-02
PACS:O212.7
基金资助:国家自然科学基金(11671275),2018年度安徽省教育厅自然科学研究重点项目(KJ2018A0390)资助.

引用本文:
刘君娥, 周洁. Case-cohort设计下多类型事件数据的一类有效估计[J]. 应用数学学报, 2018, 41(4): 433-446. LIU June, ZHOU Jie. An Effective Estimating for Case-cohort Designs with Multiple Type Event Data. Acta Mathematicae Applicatae Sinica, 2018, 41(4): 433-446.
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