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首页> 外文期刊>Emerging Themes in Epidemiology >The impact of missing data on analyses of a time-dependent exposure in a longitudinal cohort: a simulation study
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The impact of missing data on analyses of a time-dependent exposure in a longitudinal cohort: a simulation study

机译:缺失数据对纵向队列中时间相关暴露分析的影响:模拟研究

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Background Missing data often cause problems in longitudinal cohort studies with repeated follow-up waves. Research in this area has focussed on analyses with missing data in repeated measures of the outcome, from which participants with missing exposure data are typically excluded. We performed a simulation study to compare complete-case analysis with Multiple imputation (MI) for dealing with missing data in an analysis of the association of waist circumference, measured at two waves, and the risk of colorectal cancer (a completely observed outcome).
机译:背景资料的缺失通常会导致纵向队列研究出现问题,并伴随反复的随访。该领域的研究重点是在重复测量结果中缺少数据的分析,通常从中排除暴露数据缺失的参与者。我们进行了一项模拟研究,以比较完整病例分析与多重插补(MI),以分析在两次波浪测量的腰围和结直肠癌风险(完全观察到的结果)之间的关联分析中丢失的数据。

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