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针对数据有限的多分类暴露变量的不精确分类校正标准化率比。

Correcting standardized rate ratios for imprecise classification of a polychotomous exposure variable with limited data.

作者信息

Rosenbaum W L, Sterling T D, Weinkam J J

机构信息

Simon Fraser University, School of Computing Science, Burnaby, British Columbia, Canada.

出版信息

Am J Epidemiol. 1995 Aug 15;142(4):442-5. doi: 10.1093/oxfordjournals.aje.a117653.

Abstract

The analysis of exposure misclassification has received considerable attention in the epidemiologic literature, with the result that methods for correcting many summary risk estimates for such misclassification are well known. However, the application of such methods typically requires more data than are usually published (for example, the complete set of exposure- and age-specific mortality rates). The authors show, under the assumption that exposure misclassification occurs independently of disease status and confounder level, that it is possible to obtain estimates of standardized rate ratios corrected for a given pattern of misclassification from only the published standardized risk ratios and the misclassification matrix. This technique allows readers of scientific literature to perform post hoc sensitivity analysis of published risk estimates.

摘要

暴露错误分类的分析在流行病学文献中受到了相当多的关注,结果是校正此类错误分类的许多汇总风险估计值的方法广为人知。然而,应用这些方法通常需要比通常发表的数据更多的数据(例如,暴露和年龄特异性死亡率的完整数据集)。作者表明,在暴露错误分类独立于疾病状态和混杂因素水平发生的假设下,仅从已发表的标准化风险比和错误分类矩阵就有可能获得针对给定错误分类模式校正后的标准化率比估计值。这项技术使科学文献的读者能够对已发表的风险估计值进行事后敏感性分析。

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