HAZARD RATE MODELS WITH COVARIATES
HAZARD RATE MODELS WITH COVARIATES
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DOI：
10.2307/2529934
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发表时间：
1979-01-01
期刊：
影响因子：
1.9
通讯作者：
KALBFLEISCH, JD
中科院分区：
文献类型：
--
作者：
PRENTICE, RL;KALBFLEISCH, JD
许多问题，特别是在[人类]医学研究中，涉及某些协变量与事件发生时间之间的关系。危险或故障率函数提供了一种概念上简单的发生时间数据表示法，该表示法易于适应，以包括竞争风险和协变量等随时间变化的概括。两个部分参数模型的危险函数被认为是。这些是考克斯（1972）的比例风险模型和对数线性或加速失效时间模型。对关于根据这些模型在前瞻性抽样下进行估计的文献的综合分析表明，虽然在过去十年中取得了重要进展，但在分布理论、拟合检验、稳健性和充分利用允许非标准特征的方法等专题上仍需作出进一步努力。在各种其他抽样方案下应用相同的模型，可以进行大量富有成效的研究。对病例对照研究估计的讨论说明了这一点。
Many problems, particularly in [human] medical research, concern the relationship between certain covariates and the time to occurrence of an event. The hazard or failure rate function provides a conceptually simple representation of time to occurrence data that readily adapts to include such generalizations as competing risks and covariates that vary with time. Two partially parametric models for the hazard function are considered. These are the proportional hazards model of Cox (1972) and the class of log-linear or accelerated failure time models. A synthesis of the literature on estimation from these models under prospective sampling indicates that, although important advances have occurred during the past decade, further effort is warranted on such topics as distribution theory, tests of fit, robustness and the full utilization of a methodology that permits non-standard features. A good deal of fruitful research could be done on applying the same models under a variety of other sampling schemes. A discussion of estimation from case-control studies illustrates this point.