Accelerated failure time model for arbitrarily censored data with smoothed error distribution
Accelerated failure time model for arbitrarily censored data with smoothed error distribution
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DOI：
10.1198/106186005x63734
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发表时间：
2005-09-01
影响因子：
2.4
通讯作者：
Hilton, JF
中科院分区：
文献类型：
--
作者：
Kom치rek, A;Lesaffre, E;Hilton, JF
本文开发了一个半参数程序，以估计加速故障时间模型的参数。为了表达误差分布的密度，我们使用P-Spline（带惩罚）平滑技术的P-Spline。为了通过无限支撑（出于其他原因）适应错误密度，我们随着b-Spline的程度替换了b-splines的限制；即，正常密度。样条系数以及任何数量的回归参数都是通过惩罚最大似然迅速而准确估算的。该方法直接为协变量的固定值提供了预测性生存分布，同时允许进行左，右和间隔进行的数据。该方法已作为R软件包实施，并在此处应用于在间隔审查的情况下预测无艾滋病生存的问题。
This article develops a semiparametric procedure to estimate parameters of an accelerated failure time model. To express the density of the error distribution, we use the P-spline (B-splines with penalties) smoothing technique. To accommodate error densities with infinite support (and for other reasons) we replace the B-splines with their limits as the degree of the B-spline goes to infinity; namely, with normal densities. The spline coefficients as well as any number of regression parameters are quickly and accurately estimated via penalized maximum likelihood. The method directly provides predictive survival distributions for fixed values of covariates while allowing for left-, right-, and interval-censored data. The approach has been implemented as an R package and is applied here to the problem of predicting AIDS-free survival in the presence of interval censoring.