SEMIPARAMETRIC ANALYSIS OF THE ADDITIVE RISK MODEL
SEMIPARAMETRIC ANALYSIS OF THE ADDITIVE RISK MODEL
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DOI：
10.1093/biomet/81.1.61
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发表时间：
1994-03-01
期刊：
影响因子：
2.7
通讯作者：
YING, ZL
中科院分区：
文献类型：
--
作者：
LIN, DY;YING, ZL
与比例风险模型不同，累加风险模型规定，与一组可能随时间变化的协变量相关的风险函数是基线风险函数和协变量回归函数的和，而不是其乘积。与比例风险模型相比，该公式描述了协变量与故障时间之间的不同方面，并且在许多应用中比比例风险模型更可信。本文给出了具有未知基线风险函数的加性风险模型下回归参数的简单而高效的推断方法。对特定对象的生存估计也进行了研究。所提出的技术类似于比例风险模型的基于偏似然的方法。最后给出了一个实例。
In contrast to the proportional hazards model, the additive risk model specifies that the hazard function associated with a set of possibly time-varying covariates is the sum of, rather than the product of, the baseline hazard function and the regression function of covariates. This formulation describes a different aspect of the association between covariates and the failure time than the proportional hazards model, and is more plausible than the latter for many applications. In the present paper, simple procedures with high efficiencies are developed for making inference about the regression parameters under the additive risk model with an unspecified baseline hazard function. The subject-specific survival estimation is also studied. The proposed techniques resemble the partial-likelihood-based methods for the proportional hazards model. A real example is provided.