文章摘要
刘 宇,李 霓*.右删失数据下半参数线性转换模型的经验似然推断[J].海南师范大学学报自科版,2020,(4):374-381
右删失数据下半参数线性转换模型的经验似然推断
Empirical Likelihood Method for Analyzing Right-censored Data inLinear Transformation Models
  
DOI:10.12051/j.issn.1674-4942.2020.04.002
中文关键词: 右删失数据  Buckley-James方程  经验似然方法
英文关键词: right-censored data  Buckley-James equation  empirical likelihood method
基金项目:海南省自然科学基金高层次人才项目(2019RC176);国家自然科学基金项目(11861030)
作者单位
刘 宇,李 霓* 海南师范大学 数学与统计学院海南 海口 571158 
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中文摘要:
      右删失数据是删失数据中最常见的数据类型,通常出现于临床试验、生命科学、医药追 踪研究等领域,由于外在条件的局限性以及观测个体在开始或结束试验时存在差异性,导致实验 中出现右删失数据。在右删失数据下,文章基于Buckley-James方程对回归参数进行经验似然推 断,并证明所提出的调整经验似然比统计量收敛于标准的卡方分布,进而得到回归参数的置信区 间,最后进行了数值模拟研究,模拟结果显示所提出的经验似然方法优于基于KSV方法的经验似 然方法。
英文摘要:
      Right-censored data is the most common type of the censored data, which usually appears in clinical trials, life sciences, medical tracking research and other fields, due to the limitations of external conditions and the differences be⁃ tween the observed individuals at the beginning or the end of the trial, right-censored data appears. This paper makes em⁃ pirical likelihood inference of regression parameters with right censored data based on the Buckley-James equation. We demonstrated that the proposed adjusted empirical likelihood ratio statistics converge to a standard chi-squared distribu⁃ tion and obtain confidence intervals for the regression parameter. A simulation study was carried out in this paper. The sim⁃ ulation results show that the proposed empirical likelihood method in this paper was better than the empirical likelihood method based on KSV approach.
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