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Two-phase outcome-dependent studies for failure times and testing for effects of expensive covariates

机译:两阶段取决于结果的故障时间研究,并测试昂贵的协变量的影响

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摘要

Two- or multi-phase study designs are often used in settings involving failure times. In most studies, whether or not certain covariates are measured on an individual depends on their failure time and status. For example, when failures are rare, case-cohort or case-control designs are used to increase the number of failures relative to a random sample of the same size. Another scenario is where certain covariates are expensive to measure, so they are obtained only for selected individuals in a cohort. This paper considers such situations and focuses on cases where we wish to test hypotheses of no association between failure time and expensive covariates. Efficient score tests based on maximum likelihood are developed and shown to have a simple form for a wide class of models and sampling designs. Some numerical comparisons of study designs are presented.
机译:两阶段或多阶段研究设计通常用于涉及故障时间的环境中。在大多数研究中,是否对个体测量某些协变量取决于其失效时间和状态。例如,当失败很少发生时,案例队列或案例控制设计用于增加失败次数,相对于相同大小的随机样本。另一种情况是某些协变量的测量成本很高,因此仅针对队列中的选定个体才能获得它们。本文考虑了这种情况,并重点研究了我们希望检验故障时间与昂贵协变量之间没有关联的假设的情况。开发了基于最大似然的有效分数测试,并证明其具有适用于各种模型和抽样设计的简单形式。介绍了研究设计的一些数值比较。

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