Considerations for analysis of time-to-event outcomes measured with error: Bias and correction with SIMEX.
Considerations for analysis of time-to-event outcomes measured with error: Bias and correction with SIMEX.
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DOI：
10.1002/sim.7554
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发表时间：
2018-04-15
影响因子：
2
通讯作者：
Shaw PA
中科院分区：
文献类型：
--
作者：
Oh EJ;Shepherd BE;Lumley T;Shaw PA
对于时间到事件的结果，存在大量关于回归模型（如Cox模型）中协变量测量误差引入的偏差以及解决该偏差的分析方法的文献。相比之下，对了解故障时间结果中的影响或处理错误的关注较少。对于许多疾病，感兴趣的事件（如无进展生存期或艾滋病进展时间）的时间可能难以评估或依赖于自我报告，因此容易出现测量误差。对于线性模型，众所周知，结果变量中的随机误差不会使回归估计偏倚。然而，对于非线性模型，即使是随机误差或错误分类也会在估计参数中引入偏差。我们比较了两种常见的回归模型，Cox和Weibull模型，在失效时间结果的测量误差设置的性能。我们介绍了SIMEX方法的扩展，以纠正Cox模型中风险比估计的偏差，并讨论了其他分析选项，以解决响应中的测量误差。给出了对数线性生存模型在事件时间内由经典测量误差引起的风险比偏差的估计公式。提出了详细的数值研究，以检验所提出的SIMEX方法在不同水平和参数形式的误差结果下的性能。我们进一步用范德比尔特综合护理诊所艾滋病毒结果的观察数据说明了这种方法。
For time-to-event outcomes, a rich literature exists on the bias introduced by covariate measurement error in regression models, such as the Cox model, and methods of analysis to address this bias. By comparison, less attention has been given to understanding the impact or addressing errors in the failure time outcome. For many diseases, the timing of an event of interest (such as progression-free survival or time to AIDS progression) can be difficult to assess or reliant on self-report and therefore prone to measurement error. For linear models, it is well known that random errors in the outcome variable do not bias regression estimates. With non-linear models, however, even random error or misclassification can introduce bias into estimated parameters. We compare the performance of two common regression models, the Cox and Weibull models, in the setting of measurement error in the failure time outcome. We introduce an extension of the SIMEX method to correct for bias in hazard ratio estimates from the Cox model and discuss other analysis options to address measurement error in the response. A formula to estimate the bias induced into the hazard ratio by classical measurement error in the event time for a log-linear survival model is presented. Detailed numerical studies are presented to examine the performance of the proposed SIMEX method under varying levels and parametric forms of the error in the outcome. We further illustrate the method with observational data on HIV outcomes from the Vanderbilt Comprehensive Care Clinic.
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影响因子：
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作者：
Duda, Stephany N.;Shepherd, Bryan E.;McGowan, Catherine C.
通讯作者：
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通讯作者：
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