Computationally simple accelerated failure time regression for interval censored data
Computationally simple accelerated failure time regression for interval censored data
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DOI：
10.1093/biomet/88.3.703
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发表时间：
2001-09-01
期刊：
影响因子：
2.7
通讯作者：
Tsiatis, AA
中科院分区：
文献类型：
--
作者：
Betensky, RA;Rabinowitz, D;Tsiatis, AA
提出了一种不需要计算分布函数在残差处的非参数极大似然估计的方法来拟合加速失效时间模型。这种方法包括估计用同一个人的检查时间计算出的方程，就好像它们实际上是从不同的个人那里得到的一样。然后在计算回归系数的标准误差时考虑从同一个体获得的不同测量值之间的相关性。该方法适用于无论失效时间是否发生，都继续进行检测的设置中的间隔截尾数据。模拟被提出来评估该方法的行为，并通过应用于艾滋病临床试验的数据来说明该方法。
An approach is presented for fitting the accelerated failure time model to interval censored data that does not involve computing the nonparametric maximum likelihood estimate of the distribution function at the residuals. The approach involves estimating equations computed with the examination times from the same individual treated as if they had actually been obtained from different individuals. The dependence between different measurements obtained from the same individual is then accounted for in the calculation of the standard error of the regression coefficients. The approach is applicable to interval censored data in settings in which examinations continue to occur regardless of whether the failure time has occurred. Simulations are presented to assess the behaviour of the approach, and the methodology is illustrated through an application to data from an AIDS clinical trial.