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使用对数线性模型对带有协变量的区间删失生存数据进行回归分析。

Regression analysis of interval-censored survival data with covariates using log-linear models.

作者信息

Kim D K

机构信息

Department of Biostatistics, Yonsei University College of Medicine, Seoul, Korea.

出版信息

Biometrics. 1997 Dec;53(4):1274-83.

PMID:9423249
Abstract

We considered the regression analysis of the event time data with left-, right-, or interval-censored observations. We extended life-table techniques for censored survival data using log-linear models to incorporate interval-censored failures. The EM algorithm was used to calculate maximum likelihood estimates for the parameters. We assumed that the hazard function was a stepwise function over disjoint intervals of time; thus, the nonparametric model, the parametric exponential model, and the semiparametric Cox proportional hazard model were easily implemented as special cases. We adapted the restricted EM algorithm to test hypotheses and to construct confidence intervals for the parameters. These methods were applied in an analysis of the recurrence time for treated melanoma patients.

摘要

我们考虑了对具有左删失、右删失或区间删失观测值的事件时间数据进行回归分析。我们使用对数线性模型扩展了用于删失生存数据的寿命表技术,以纳入区间删失失败情况。期望最大化(EM)算法用于计算参数的最大似然估计值。我们假设风险函数在不相交的时间区间上是一个阶梯函数;因此,非参数模型、参数指数模型和半参数Cox比例风险模型作为特殊情况很容易实现。我们采用受限EM算法来检验假设并构建参数的置信区间。这些方法应用于对接受治疗的黑色素瘤患者复发时间的分析。

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