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Analysis of dependently truncated data in Cox framework

机译:在Cox框架中分析依赖截断的数据

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摘要

Truncation is a known feature of bone marrow transplant (BMT) registry data, for which the survival time of a leukemia patient is left truncated by the waiting time to transplant. It was recently noted that a longer waiting time was linked to poorer survival. A straightforward solution is a Cox model on the survival time with the waiting time as both truncation variable and covariate. The Cox model should also include other recognized risk factors as covariates. In this article, we focus on estimating the distribution function of waiting time and the probability of selection under the aforementioned Cox model.
机译:截断是骨髓移植(BMT)注册表数据的已知功能,对于该患者,白血病患者的生存时间会被等待移植的时间截断。最近有人指出,更长的等待时间与较差的生存率有关。一个简单的解决方案是将生存时间与等待时间同时作为截断变量和协变量的Cox模型。 Cox模型还应包括其他公认的风险因素作为协变量。在本文中,我们着重估计上述Cox模型下的等待时间分布函数和选择概率。

著录项

  • 来源
    《Communications in Statistics》 |2018年第7期|1677-1695|共19页
  • 作者

    Liu Yang; Li Ji; Zhang Xu;

  • 作者单位

    Univ Oklahoma, Hlth Sci Ctr, Dept Biostat & Epidemiol, Oklahoma City, OK USA;

    Univ Texas Hlth Sci Ctr Houston, CCTS, BERD Component, Houston, TX 77030 USA;

    US Ctr Dis Control & Prevent, Div Anal Res & Practice Integrat, Natl Ctr Injury Prevent & Control, Atlanta, GA USA;

    Univ Texas Hlth Sci Ctr Houston, Div Clin & Translat Sci, Dept Internal Med, Houston, TX 77030 USA;

  • 收录信息 美国《科学引文索引》(SCI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Cox model; Dependent truncation; Inverse probability weighting;

    机译:Cox模型;相关截断;逆概率加权;

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