协变量
加速失效时间模型
比例危险模型
生存分析
统计
计量经济学
计算机科学
对数
回归分析
生存功能
数学
数学分析
标识
DOI:10.1002/sim.4780111409
摘要
Abstract For the past two decades the Cox proportional hazards model has been used extensively to examine the covariate effects on the hazard function for the failure time variable. On the other hand, the accelerated failure time model, which simply regresses the logarithm of the survival time over the covariates, has seldom been utilized in the analysis of censored survival data. In this article, we review some newly developed linear regression methods for analysing failure time observations. These procedures have sound theoretical justification and can be implemented with an efficient numerical method. The accelerated failure time model has an intuitive physical interpretation and would be a useful alternative to the Cox model in survival analysis.
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