Pan W
Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
Lifetime Data Anal. 2001 Mar;7(1):55-64. doi: 10.1023/a:1009625210191.
The accelerated failure time (AFT) model is an important alternative to the Cox proportional hazards model (PHM) in survival analysis. For multivariate failure time data we propose to use frailties to explicitly account for possible correlations (and heterogeneity) among failure times. An EM-like algorithm analogous to that in the frailty model for the Cox model is adapted. Through simulation it is shown that its performance compares favorably with that of the marginal independence approach. For illustration we reanalyze a real data set.
加速失效时间(AFT)模型是生存分析中Cox比例风险模型(PHM)的重要替代方法。对于多变量失效时间数据,我们建议使用脆弱性来明确考虑失效时间之间可能的相关性(和异质性)。我们采用了一种类似于Cox模型脆弱性模型中的类期望最大化(EM)算法。通过模拟表明,其性能优于边际独立性方法。为了说明,我们重新分析了一个真实数据集。