MAXIMUM-LIKELIHOOD-ESTIMATION FOR INTERVAL-CENSORED DATA USING A WEIBULL-BASED ACCELERATED FAILURE TIME MODEL
MAXIMUM-LIKELIHOOD-ESTIMATION FOR INTERVAL-CENSORED DATA USING A WEIBULL-BASED ACCELERATED FAILURE TIME MODEL
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DOI：
10.2307/2532360
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发表时间：
1992-09-01
期刊：
影响因子：
1.9
通讯作者：
DAGOSTINO, RB
中科院分区：
文献类型：
--
作者：
ODELL, PM;ANDERSON, KM;DAGOSTINO, RB
加速失效时间回归模型最常用于右删失生存数据。本文研究了基于威布尔的加速失效时间回归模型在左截尾数据和区间截尾数据下的应用。考虑了两种可供选择的分析方法。首先计算观测截尾模式的最大似然估计(MLE)。这些与用中点取代左删失和区间删失数据的估计(中点估计，或MDE)进行了比较。仿真研究表明，在样本相对较大的情况下，MLE优于MDE的情况较多。对于风险率持平或接近持平的样本，或者区间删失数据的百分比很小的样本，MDE是足够的。文中还讨论了一个使用弗雷明翰心脏研究数据的例子。
The accelerated failure time regression model is most commonly used with right-censored survival data. This report studies the use of a Weibull-based accelerated failure time regression model when left- and interval-censored data are also observed. Two alternative methods of analysis are considered. First, the maximum likelihood estimates (MLEs) for the observed censoring pattern are computed. These are compared with estimates where midpoints are substituted for left- and interval-censored data (midpoint estimator, or MDE). Simulation studies indicate that for relatively large samples there are many instances when the MLE is superior to the MDE. For samples where the hazard rate is flat or nearly so, or where the percentage of interval-censored data is small, the MDE is adequate. An example using Framingham Heart Study data is discussed.