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Effect of Berkson measurement error on parameter estimates in Cox regression models

机译:Berkson测量误差对Cox回归模型参数估计的影响

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摘要

We study the effect of additive and multiplicative Berkson measurement error in Cox proportional hazard model. By plotting the true and the observed Survivor function and the true and the observed hazard function dependent on the exposure one can get ideas about the effect of this type of error on the estimation of the slope parameter corresponding to the variable measured with error. As an example we analyze the measurement error in the situation of the German Uranium Miners Study both with the graphical methods and with a simulation study. We do not see a substantial bias in the presence of small measurement error and in the rare disease case. Ever the effect of a Berkson measurement error with high variance, which is not unrealistic in our example, is a negligible attentuation of the observed effect. This effect is more pronounced for multiplicative measurement error.
机译:我们研究了Cox比例风险模型中加性和乘性Berkson测量误差的影响。通过绘制真实的和观察到的幸存者函数以及真实的和观察到的危险函数(取决于暴露),可以了解有关这种类型的误差对与误差测量的变量相对应的斜率参数估计的影响。例如,我们通过图形方法和模拟研究来分析德国铀矿工研究情况下的测量误差。在存在较小的测量误差和罕见疾病的情况下,我们没有看到明显的偏差。具有高方差的伯克森测量误差的影响,在我们的示例中并非不现实,对观察到的影响的忽略可以忽略不计。对于乘法测量误差,这种影响更为明显。

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