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多重填补法在流行病学文献中的应用。

Use of multiple imputation in the epidemiologic literature.

作者信息

Klebanoff Mark A, Cole Stephen R

机构信息

Division of Epidemiology, Statistics, and Prevention Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD 20892-7510, USA.

出版信息

Am J Epidemiol. 2008 Aug 15;168(4):355-7. doi: 10.1093/aje/kwn071. Epub 2008 Jun 30.

Abstract

The authors attempted to catalog the use of procedures to impute missing data in the epidemiologic literature and to determine the degree to which imputed results differed in practice from unimputed results. The full text of articles published in 2005 and 2006 in four leading epidemiologic journals was searched for the text imput. Sixteen articles utilizing multiple imputation, inverse probability weighting, or the expectation-maximization algorithm to impute missing data were found. The small number of relevant manuscripts and diversity of detail provided precluded systematic analysis of the use of imputation procedures. To form a bridge between current and future practice, the authors suggest details that should be included in articles that utilize these procedures.

摘要

作者试图梳理流行病学文献中用于估算缺失数据的方法,并确定估算结果在实际应用中与未估算结果的差异程度。检索了2005年和2006年发表在四种主要流行病学杂志上的文章全文,查找与“估算”相关的文本。共发现16篇文章使用多重填补、逆概率加权或期望最大化算法来估算缺失数据。相关手稿数量较少且提供的细节多样,使得无法对估算方法的使用进行系统分析。为了在当前和未来的实践之间架起一座桥梁,作者建议在使用这些方法的文章中应包含的细节。

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