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

By Shona Fielding, Peter Fayers, Alison Mary McDonald, Gladys Campbell McPherson, Marion Kay Campbell and RECORD Study Group


Objective: QoL data were routinely collected in a randomised controlled trial (RCT), which\ud employed a reminder system, retrieving about 50% of data originally missing. The objective was to\ud use this unique feature to evaluate possible missingness mechanisms and to assess the accuracy of simple imputation methods.\ud Methods: Those patients responding after reminder were regarded as providing missing\ud responses. A hypothesis test and a logistic regression approach were used to evaluate the\ud missingness mechanism. Simple imputation procedures were carried out on these missing scores\ud and the results compared to the actual observed scores.\ud 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\ud procedures utilising information collected close to the point of imputation (last value carried\ud forward, next value carried backward and last-and-next), were the best methods in this setting.\ud However, although these methods were the best of the simple imputation procedures considered,\ud they were not sufficiently accurate to be confident of obtaining unbiased results under imputation.\ud Conclusion: The use of the reminder data enabled the conclusion of possible MNAR data.\ud 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.The MRC funded the central organisation of RECORD, and Shire Pharmaceuticals Group plc funded the drugs, which were manufactured by Nycomed Ltd. The Health Services Research Unit is funded by the Chief Scientist Office of the Scottish Government Health Directorate. Shona Fielding is also currently funded by the Chief Scientist Office on a Research Training Fellowship (CZF/1/31)Peer reviewedPublisher PD

Topics: Data Interpretation, Statistical, Quality of Life, Questionnaires, RA Public aspects of medicine
Publisher: BMC
Year: 2008
DOI identifier: 10.1186/1477-7525-6-57
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