Kristensen P
National Institute of Occupational Health, Oslo, Norway.
Epidemiology. 1992 May;3(3):210-5. doi: 10.1097/00001648-199205000-00005.
When misclassification of exposure and disease is nondifferential but not independent of one another, bias away from the null can result. For dichotomous variables, misclassification is nonindependent when the probability of misclassification of one variable is dependent on the correctness of classification of the other variable. One plausible form of nonindependent misclassification may result from variation in the threshold for reporting exposure and outcome by study subjects. The odds ratio after dependent misclassification can be expressed as a function of the true odds ratio, the prevalences of exposure and outcome, and the probabilities of misclassification. When prevalences of exposure and outcome are low, bias may be considerable even at low probabilities of misclassification. The nonindependent misclassification described in this article will result in a positive bias in the odds ratio and is therefore of prime concern when questioning the validity of an observed effect. The core of the problem lies in the study design and can be solved by eliminating the common link that makes nonindependent errors possible.
当暴露和疾病的错误分类是非差异的但并非相互独立时,可能会导致偏离无效值的偏倚。对于二分变量,当一个变量的错误分类概率取决于另一个变量的分类正确性时,错误分类就是非独立的。非独立错误分类的一种可能形式可能源于研究对象报告暴露和结局的阈值存在差异。相关错误分类后的比值比可以表示为真实比值比、暴露和结局的患病率以及错误分类概率的函数。当暴露和结局的患病率较低时,即使错误分类概率较低,偏倚也可能相当大。本文所述的非独立错误分类将导致比值比出现正向偏倚,因此在质疑观察到的效应的有效性时,这是首要关注的问题。问题的核心在于研究设计,可以通过消除使非独立错误成为可能的共同关联来解决。