Flegal K M, Keyl P M, Nieto F J
Division of Health Examination Statistics, Centers for Disease Control, Hyattsville, MD.
Am J Epidemiol. 1991 Nov 15;134(10):1233-44. doi: 10.1093/oxfordjournals.aje.a116026.
Misclassification into exposure categories formed from a continuous variable arises from measurement error in the continuous variable. Examples and mathematical results are presented to show that if the measurement error is nondifferential (independent of disease status), the resulting misclassification will often be differential, even in cohort studies. The degree and direction of differential misclassification vary with the exposure distribution, the category definitions, the measurement error distribution, and the exposure-disease relation. Failure to recognize the likelihood of differential misclassification may lead to incorrect conclusions about the effects of measurement error on estimates of relative risk when categories are formed from continuous variables, such as dietary intake. Simulations were used to examine some effects of nondifferential measurement error. Under the conditions used, nondifferential measurement error reduced relative risk estimates, but not to the degree predicted by the assumption of nondifferential misclassification. When relative risk estimates were corrected using methods appropriate for nondifferential misclassification, the "corrected" relative risks were almost always higher than the true relative risks, sometimes considerably higher. The greater the measurement error, the more inaccurate was the correction. The effects of exposure measurement errors need more critical evaluation.
将连续变量划分为暴露类别时出现的错误分类源于该连续变量的测量误差。本文给出了示例和数学结果,以表明如果测量误差是非差异性的(与疾病状态无关),那么即使在队列研究中,由此产生的错误分类往往也是差异性的。差异性错误分类的程度和方向会因暴露分布、类别定义、测量误差分布以及暴露 - 疾病关系而有所不同。当从连续变量(如饮食摄入量)形成类别时,如果未能认识到存在差异性错误分类的可能性,可能会导致关于测量误差对相对风险估计值影响的错误结论。通过模拟来检验非差异性测量误差的一些影响。在所采用的条件下,非差异性测量误差降低了相对风险估计值,但降低程度并非如非差异性错误分类假设所预测的那样。当使用适用于非差异性错误分类的方法校正相对风险估计值时,“校正后的”相对风险几乎总是高于真实的相对风险,有时高出很多。测量误差越大,校正就越不准确。暴露测量误差的影响需要更严格的评估。