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中国临床药理学与治疗学 ›› 2011, Vol. 16 ›› Issue (11): 1266-1271.

• 定理药理学 • 上一篇    下一篇

同秩和高比例删失情况下多组生存率的比较

李婵娟, 王锐, 蒋志伟, 夏结来   

  1. 第四军医大学卫生统计学教研室,西安 710032,陕西
  • 收稿日期:2011-07-08 修回日期:2011-09-05 出版日期:2011-11-26 发布日期:2011-11-29
  • 通讯作者: 夏结来,男,教授,博士生导师,主要从事临床试验统计学方法研究。Tel: 029-84774904 E-mail: jielaixia@yahoo.com
  • 作者简介:李婵娟,女,博士,讲师,主要从事临床试验统计学方法研究。Tel: 029-84772180 E-mail: chanjuan_li@sohu.com
  • 基金资助:
    国家自然科学基金资助项目(81001290)

Comparison on multiple survival rates based on tied and heavy censoring data

LI Chan-juan, WANG Rui, JIANG Zhi-wei, XIA Jie-lai   

  1. Department of Health Statistics, Fourth Military Medical University, Xi'an 710032, Shaanxi, China
  • Received:2011-07-08 Revised:2011-09-05 Online:2011-11-26 Published:2011-11-29

摘要: logrank检验和Cox模型常被用来比较多组生存率间的差别。如果同秩和一组全部删失特殊情况下仍采用常规模型有可能会得出错误结论。该如何分析同秩和高比例删失数据是需要研究的问题。本文通过一临床实例的分析过程,探讨了Discrete、Breslow、Efron和Exact四种方法处理同秩现象的效果,当时间为离散型推荐使用Discrete方法,否则推荐使用Exact方法。当一组全部删失,Cox模型的Wald检验结果不可靠,Cox模型的LR检验和Score检验或logrank检验结果较为可取,或者直接考虑采用χ2检验对观察终点的生存率进行比较。

关键词: logrank检验, Cox模型, 同秩, 高比例删失

Abstract: Logrank test and Cox model were usually applied to compare multiple survival rates. A mistake maybe takes when data are tied or/and all data are censor. How to analyze these data is a problem. Based on a clinical trial example, Discrete, Breslow, Efron and Exact methods were discussed with tied data. Discrete method is best when time is discrete. Otherwise, Exact is best. In addition, data analysis with heavy censoring was explored. When one group is total censor Wald test is unreliable. However, LR test and Score test or logrank test is acceptable. Chi-square test is another choice to analyze survival rates with heavy censoring.

Key words: Logrank test, Cox model, Ties, Heavy censoring

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