Effect of Berkson measurement error on parameter estimates in Cox regression models.
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 Cohort Study both with 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. Even the effect of a Berkson measurement error with high variance, which is not unrealistic in our example, is a negligible attenuation of the observed effect. However, this effect is more pronounced for multiplicative measurement error.
Küchenhoff
Helmut
H
Department of Statistics, Ludwig-Maximilians-Universität, Akademiestr. 1, 80799, München, Germany. kuechenhoff@stat.uni-muenchen.de
Bender
Ralf
R
Langner
Ingo
I
D000293:Adolescent; D000328:Adult; D015982:Bias; D015331:Cohort Studies; D005858:Germany; D006801:Humans; D008297:Male; D008906:Mining; D016273:Occupational Exposure / Q000706:statistics & numerical data*; D016016:Proportional Hazards Models; D011886:Radon / Q000032:analysis*; D014501:Uranium
D014501:Uranium; D011886:Radon