Does adjustment for non-differential misclassification of dichotomous exposure induce positive bias if there is no true association?

Igor Burstyn
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Abstract

This article is a response to an off-the-record discussion that I had at an international meeting of epidemiologists more than decade ago. It centered on a concern, perhaps widely spread, that adjustment for exposure misclassification can induce a false positive result. I trace the possible history of this supposition and test it in a simulated case-control study under the assumption of non-differential misclassification of binary exposure, in which a Bayesian adjustment is applied. Probabilistic bias analysis is also briefly considered. The main conclusion is that adjustment for the presumed non-differential exposure misclassification of dichotomous does not “induce” positive associations, especially if the focus of the interpretation of the result is taken away from the point estimate. The misconception about positive bias induced by adjustment for exposure misclassification, if more clearly explained during the training of epidemiologists, may promote appropriate (and wider) use of the adjustment techniques. The simple message that can be derived from this paper is: “Exposure misclassification as a tractable problem that deserves much more attention than just a typical qualitative throw-away discussion”.

如果不存在真正的关联,对二分暴露的非差异性误分类进行调整是否会引起正偏差?
这篇文章是对我十多年前在一次国际流行病学家会议上的一次非正式讨论的回应。讨论的焦点是一种可能广为流传的担忧,即对暴露误分类的调整可能会导致假阳性结果。我追溯了这一假设的可能历史,并在一项模拟病例对照研究中对其进行了检验,该研究假定二元暴露无差别误分类,并应用了贝叶斯调整法。此外,还简要考虑了概率偏差分析。主要结论是,对假定的非差异性二元暴露误分类进行调整并不会 "诱发 "正相关,特别是如果对结果的解释重点脱离了点估计。如果在对流行病学家进行培训时能更清楚地解释对暴露误分类进行调整所引起的正偏倚这一误解,可能会促进调整技术的适当(和更广泛)使用。从这篇论文中我们可以得到一个简单的信息:"暴露误分类是一个可以解决的问题,值得更多的关注,而不仅仅是一个典型的定性讨论"。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Global Epidemiology
Global Epidemiology Medicine-Infectious Diseases
CiteScore
5.00
自引率
0.00%
发文量
22
审稿时长
39 days
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