Marshall R J
Department of Community Health, University of Auckland, New Zealand.
Epidemiology. 1994 May;5(3):309-14. doi: 10.1097/00001648-199405000-00009.
Misclassification of a binary exposure in case-control studies is usually assessed by sensitivity and specificity of the measured exposure. Sensitivity and specificity do not adequately measure the degree of misclassification because they assess only the proportion of truly exposed (or unexposed) subjects who are misclassified by the defective measurement. They do not account for the proportion of subjects, categorized by the defective measurement as either exposed or unexposed, who are misclassified, in other words, the predictive value of the measurement. A more appropriate way of measuring misclassification is by "quality indices" that take both of these criteria into account and that are essentially rescaled sensitivity and specificity, or predictive value, measures. I present the relation between measured and actual odds ratios in terms of quality indices. If quality indices are nondifferential or proportional, there is no misclassification bias to the odds ratio. The relation offers a new approach to correcting measured odds ratios.
病例对照研究中二元暴露的错误分类通常通过所测量暴露的敏感性和特异性来评估。敏感性和特异性并不能充分衡量错误分类的程度，因为它们仅评估被有缺陷测量误分类的真正暴露（或未暴露）受试者的比例。它们没有考虑到被有缺陷测量分类为暴露或未暴露的受试者中被误分类的比例，换句话说，即测量的预测值。一种更合适的测量错误分类的方法是通过“质量指标”，这些指标同时考虑了这两个标准，并且本质上是重新调整后的敏感性和特异性或预测值测量。我根据质量指标阐述了测量的比值比与实际比值比之间的关系。如果质量指标是非差异的或成比例的，那么对于比值比就不存在错误分类偏差。这种关系为校正测量的比值比提供了一种新方法。
