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简单的插补方法对于非随机缺失(MNAR)的生活质量数据是不够的。

Simple imputation methods were inadequate for missing not at random (MNAR) quality of life data.

作者信息

Fielding Shona, Fayers Peter M, McDonald Alison, McPherson Gladys, Campbell Marion K

机构信息

Department of Public Health, University of Aberdeen, UK.

出版信息

Health Qual Life Outcomes. 2008 Aug 4;6:57. doi: 10.1186/1477-7525-6-57.

DOI:10.1186/1477-7525-6-57
PMID:18680574
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2531086/
Abstract

OBJECTIVE

QoL data were routinely collected in a randomised controlled trial (RCT), which employed a reminder system, retrieving about 50% of data originally missing. The objective was to use this unique feature to evaluate possible missingness mechanisms and to assess the accuracy of simple imputation methods.

METHODS

Those patients responding after reminder were regarded as providing missing responses. A hypothesis test and a logistic regression approach were used to evaluate the missingness mechanism. Simple imputation procedures were carried out on these missing scores and the results compared to the actual observed scores.

RESULTS

The hypothesis test and logistic regression approaches suggested the reminder data were missing not at random (MNAR). Reminder-response data showed that simple imputation procedures utilising information collected close to the point of imputation (last value carried forward, next value carried backward and last-and-next), were the best methods in this setting. However, although these methods were the best of the simple imputation procedures considered, they were not sufficiently accurate to be confident of obtaining unbiased results under imputation.

CONCLUSION

The use of the reminder data enabled the conclusion of possible MNAR data. Evaluating this mechanism was important in determining if imputation was useful. Simple imputation was shown to be inadequate if MNAR are likely and alternative strategies should be considered.

摘要

目的

在一项采用提醒系统的随机对照试验(RCT)中常规收集生活质量(QoL)数据,该系统找回了约50%原本缺失的数据。目的是利用这一独特特征评估可能的缺失机制,并评估简单插补方法的准确性。

方法

那些在收到提醒后做出回应的患者被视为提供了缺失的回应。采用假设检验和逻辑回归方法来评估缺失机制。对这些缺失分数进行简单插补程序,并将结果与实际观察到的分数进行比较。

结果

假设检验和逻辑回归方法表明提醒数据并非随机缺失(MNAR)。提醒回应数据显示,利用在插补点附近收集的信息(向前结转最后一个值、向后结转下一个值以及前后值)的简单插补程序是这种情况下的最佳方法。然而,尽管这些方法是所考虑的简单插补程序中最好的,但它们的准确性不足以让人确信在插补下能获得无偏结果。

结论

提醒数据的使用使得能够得出可能存在非随机缺失数据的结论。评估这种机制对于确定插补是否有用很重要。如果可能存在非随机缺失,简单插补被证明是不够的,应考虑其他策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db19/2531086/caf60fec822b/1477-7525-6-57-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db19/2531086/87d00c4a3f22/1477-7525-6-57-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db19/2531086/caf60fec822b/1477-7525-6-57-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db19/2531086/87d00c4a3f22/1477-7525-6-57-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db19/2531086/caf60fec822b/1477-7525-6-57-2.jpg

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