一种采用多重填补方法，结合加法风险模型对区间删失失效时间数据进行分析的方法。
A multiple imputation approach to the analysis of interval-censored failure time data with the additive hazards model.
作者信息
Chen Ling, Sun Jianguo
机构信息
Division of Biostatistics, Washington University School of Medicine, Campus Box 8067, 660 S. Euclid Ave, St. Louis, MO 63110, USA ; Department of Statistics, University of Missouri, 146 Middlebush Hall, Columbia, MO 65211, USA.
Department of Statistics, University of Missouri, 146 Middlebush Hall, Columbia, MO 65211, USA.
出版信息
Comput Stat Data Anal. 2010 Apr 1;54(4):1109-1116. doi: 10.1016/j.csda.2009.10.022.
This paper discusses regression analysis of interval-censored failure time data, which occur in many fields including demographical, epidemiological, financial, medical, and sociological studies. For the problem, we focus on the situation where the survival time of interest can be described by the additive hazards model and a multiple imputation approach is presented for inference. A major advantage of the approach is its simplicity and it can be easily implemented by using the existing software packages for right-censored failure time data. Extensive simulation studies are conducted which indicate that the approach performs well for practical situations and is comparable to the existing methods. The methodology is applied to a set of interval-censored failure time data arising from an AIDS clinical trial.
本文讨论区间删失失效时间数据的回归分析，这类数据出现在包括人口统计学、流行病学、金融、医学和社会学研究等许多领域。针对该问题，我们关注感兴趣的生存时间可由加法风险模型描述的情形，并提出一种多重填补方法用于推断。该方法的一个主要优点是其简单性，并且可以通过使用现有的针对右删失失效时间数据的软件包轻松实现。进行了广泛的模拟研究，结果表明该方法在实际情况中表现良好，并且与现有方法相当。该方法应用于一组来自艾滋病临床试验的区间删失失效时间数据。
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