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多分类混杂因素的非差异性错误分类导致的偏倚。

Bias due to non-differential misclassification of polytomous confounders.

作者信息

Brenner H

机构信息

Unit of Epidemiology, University of Ulm, Germany.

出版信息

J Clin Epidemiol. 1993 Jan;46(1):57-63. doi: 10.1016/0895-4356(93)90009-p.

Abstract

This paper addresses potential effects of non-differential misclassification of polytomous confounders on adjusted exposure-disease associations. Although the degree of confounder-misclassification bias heavily depends on the relative distribution of the confounding variable among the compared exposure groups and the misclassification pattern, in most cases the bias is in the same direction (though to a lesser degree) than the confounding, i.e. the observed adjusted measures lie between the crude and the fully adjusted measures. In some instances, however, the confounder misclassification bias may be in the opposite direction. This is in contrast to previous understanding that non-differential confounder misclassification always tends to bias adjusted effect estimates towards the crude estimates and that the extent of this bias has a stable relationship to the degree of misclassification. Consequently, conclusions on the potential effects of non-differential misclassification of a polytomous confounder in any given study should only be made after careful sensitivity analyses which consider plausible ranges of misclassification rates.

摘要

本文探讨了多分类混杂因素的非差异性错误分类对调整后的暴露-疾病关联的潜在影响。尽管混杂因素错误分类偏差的程度在很大程度上取决于所比较的暴露组中混杂变量的相对分布以及错误分类模式,但在大多数情况下,该偏差与混杂偏差的方向相同(尽管程度较小),即观察到的调整后测量值介于粗测量值和完全调整后的测量值之间。然而,在某些情况下,混杂因素错误分类偏差可能方向相反。这与之前的认识不同,即非差异性混杂因素错误分类总是倾向于使调整后的效应估计值偏向粗估计值,并且这种偏差的程度与错误分类的程度具有稳定的关系。因此,在任何给定研究中,关于多分类混杂因素非差异性错误分类的潜在影响的结论,只有在进行仔细的敏感性分析并考虑合理的错误分类率范围之后才能得出。

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