The rise of multiple imputation: a review of the reporting and implementation of the method in medical research.
The rise of multiple imputation: a review of the reporting and implementation of the method in medical research.
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多次插补的兴起：对医学研究方法的报告和实施的综述。
DOI：
10.1186/s12874-015-0022-1
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发表时间：
2015-04-07
影响因子：
4
通讯作者：
Simpson JA
中科院分区：
文献类型：
--
作者：
Hayati Rezvan P;Lee KJ;Simpson JA
缺失数据在医学研究中很常见，如果处理不当，可能会导致统计功效的损失和潜在的偏倚结果。多重插补（MI）是一种在实践中被广泛采用的处理缺失数据的统计方法。许多学术期刊现在强调报告缺失数据信息的重要性，并发表了记录MI应用的拟议指南。本综述评价了缺失数据的报告、MI的应用（包括提供的关于插补模型的详细信息）以及医学研究文章中MI框架内敏感性分析的频率。对2008年1月至2013年12月期间在《柳叶刀》和《新英格兰医学杂志》上发表的实施MI的文章进行了系统综述。我们确定了103篇使用MI的论文，论文数量从2008年的11篇增加到2013年的26篇。近一半的论文按每个变量指定了完整案例的比例或缺失数据的比例。在大多数文章（86%）中，指定了插补变量。在38篇（37%）陈述插补方法的论文中，20篇使用链式方程，8篇使用多元正态插补，10篇使用替代方法。很少有文章（9%）详细说明了他们在插补过程中如何处理非正态分布变量。39篇论文（38%）陈述了插补模型中包含的变量。不到一半的论文（46%）报告了插补数量，只有两篇论文比较了插补数据和观察数据的分布。66篇论文将MI的结果作为次要分析。只有3篇文章在MI后进行了敏感性分析，以评估与随机缺失假设的偏离，只有一篇文章提供了敏感性分析的详细信息。该综述概述了缺失数据记录中的缺陷以及提供的插补细节。此外，只有少数文章在MI后进行了敏感性分析，尽管指南中强烈建议这样做。鼓励作者遵循现有指南，并提供有关缺失数据和插补过程的信息。本文的在线版本（doi：10.1186/s12874-015-0022-1）包含补充材料，可供授权用户使用。
Missing data are common in medical research, which can lead to a loss in statistical power and potentially biased results if not handled appropriately. Multiple imputation (MI) is a statistical method, widely adopted in practice, for dealing with missing data. Many academic journals now emphasise the importance of reporting information regarding missing data and proposed guidelines for documenting the application of MI have been published. This review evaluated the reporting of missing data, the application of MI including the details provided regarding the imputation model, and the frequency of sensitivity analyses within the MI framework in medical research articles. A systematic review of articles published in the Lancet and New England Journal of Medicine between January 2008 and December 2013 in which MI was implemented was carried out. We identified 103 papers that used MI, with the number of papers increasing from 11 in 2008 to 26 in 2013. Nearly half of the papers specified the proportion of complete cases or the proportion with missing data by each variable. In the majority of the articles (86%) the imputed variables were specified. Of the 38 papers (37%) that stated the method of imputation, 20 used chained equations, 8 used multivariate normal imputation, and 10 used alternative methods. Very few articles (9%) detailed how they handled non-normally distributed variables during imputation. Thirty-nine papers (38%) stated the variables included in the imputation model. Less than half of the papers (46%) reported the number of imputations, and only two papers compared the distribution of imputed and observed data. Sixty-six papers presented the results from MI as a secondary analysis. Only three articles carried out a sensitivity analysis following MI to assess departures from the missing at random assumption, with details of the sensitivity analyses only provided by one article. This review outlined deficiencies in the documenting of missing data and the details provided about imputation. Furthermore, only a few articles performed sensitivity analyses following MI even though this is strongly recommended in guidelines. Authors are encouraged to follow the available guidelines and provide information on missing data and the imputation process. The online version of this article (doi:10.1186/s12874-015-0022-1) contains supplementary material, which is available to authorized users.
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DOI：
10.1056/nejmoa0912321
发表时间：
2010-07-01
期刊：
The New England journal of medicine
影响因子：
--
作者：
Brott TG;Hobson RW 2nd;Howard G;Roubin GS;Clark WM;Brooks W;Mackey A;Hill MD;Leimgruber PP;Sheffet AJ;Howard VJ;Moore WS;Voeks JH;Hopkins LN;Cutlip DE;Cohen DJ;Popma JJ;Ferguson RD;Cohen SN;Blackshear JL;Silver FL;Mohr JP;Lal BK;Meschia JF;CREST Investigators
通讯作者：
CREST Investigators
DOI：
10.1056/nejmoa1001288
发表时间：
2010-07-15
期刊：
The New England journal of medicine
影响因子：
--
作者：
ACCORD Study Group;ACCORD Eye Study Group;Chew EY;Ambrosius WT;Davis MD;Danis RP;Gangaputra S;Greven CM;Hubbard L;Esser BA;Lovato JF;Perdue LH;Goff DC Jr;Cushman WC;Ginsberg HN;Elam MB;Genuth S;Gerstein HC;Schubart U;Fine LJ
通讯作者：
Fine LJ
影响因子：
168.9
作者：
Caroli, Anna;Perico, Norberto;Ruggenenti, Piero
通讯作者：
Ruggenenti, Piero
影响因子：
158.5
作者：
Armstrong, Paul W.;Gershlick, Anthony H.;Van de Werf, Frans
通讯作者：
Van de Werf, Frans
影响因子：
158.5
作者：
Feldman, Ted;Foster, Elyse;Mauri, Laura
通讯作者：
Mauri, Laura