右删失数据下加速失效模型的估计问题(英文)

The Estimation of Accelerated Failure Time Model with Right-Censored Data

加速失效模型合理地描述了协变量对失效时间的影响,但删失数据的存在对该半参数回归模型的分析带来了很大的挑战.在现有的研究中,删失数据的加速失效模型研究大多牵涉到复杂的计算.为了解决这个问题,本文采用无偏转换和K-M估计相结合的方法进行分析.对删失的响应变量构造无偏转换量,利用最小二乘方法可以得到回归系数的估计,可以证明所得到的估计具有相合性和渐近正态性.在此基础上,利用K-M估计的做法,可以得到随机误差项的分布函数的估计,文中证明了该估计具有强相合性.模拟计算的结果进一步说明了本文所用方法的可行性和估计的有效性.

The accelerated failure time model provides a natural formulation of the effects of covariates on the failure time variable. The presence of censoring poses major challenges in the semi-parametric analysis. The existing semi-parametric estimators are computationally intractable. In this arti- cle we propose an unbiased transformation for the potential censored response variable, thus least square estimators of regression parameters can be gotten easily. The resulting estimators are con- sistent and asymptotically normal. Based on these, we can get a strongly consistent K-M estimator for the distribution of random error. Extensive simulation studies show that the asymptotic ap- proximations are accurate in practical situations.