The impact of time-dependent bias in proportional hazards modelling
The impact of time-dependent bias in proportional hazards modelling
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DOI：
10.1002/sim.3437
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发表时间：
2008-12-30
影响因子：
2
通讯作者：
Schumacher, Martin
中科院分区：
文献类型：
--
作者：
Beyersmann, Jan;Wolkewitz, Martin;Schumacher, Martin
在临床文献中，时间依赖性暴露状态通常被分析为已知的时间起源。尽管统计学家同意，在分析对时间的影响时，这种分析产生了有偏差的结果，但本文是第一个详细研究比例风险分析中产生的偏差的文章。我们证明了有偏风险比估计总是小于无偏风险比估计；根据正确的对数风险比估计的符号，这会导致暴露的膨胀效应或衰减效应。我们找到了一个基于广义秩估计的渐近偏倚的显式公式，并研究了审查的作用，它可以防止个体在偏倚分析中被认为是基线暴露。我们用医院感染状况和不同审查模式的数据来说明我们的结果。版权所有(C) 2008约翰威利父子有限公司
In the clinical literature, time-dependent exposure status has regularly been analysed as if known at time origin. Although statisticians agree that such an analysis yields biased results when analysing the effect on the time until some endpoint of interest, this paper is the first to study in detail the bias arising in a proportional hazards analysis. We show that the biased hazard ratio estimate will always be less than the unbiased one; this leads to either an inflated or a damped effect of exposure, depending on the sign of the correct log hazard ratio estimate. We find an explicit formula of the asymptotic bias based on generalized rank estimators, and we investigate the role of censoring, which may prevent an individual from being considered as being baseline exposed in the biased analysis. We illustrate our results with data on hospital infection status and different censoring patterns. Copyright (C) 2008 John Wiley & Sons, Ltd.