The use and reporting of multiple imputation in medical research - a review

Background: Multiple imputation (MI) is an advanced, principled method of dealing with missing data in statistical analyses, a common problem in medical research. This paper sought to document the use of MI in general medical journals and to evaluate the information provided to readers about the application of the procedure in studies.

Methods: Research articles using MI in analyses published in JAMA, New England Journal of Medicine, BMJ and the Lancet were identified using full text searches from the earliest date each journal offered such searches until the end of 2008. Ninety-nine articles were found. Studies were classified according to their design.

Results: Multiple imputation was used in 49 RCTs and 50 other types of studies. A third of the articles (n = 33) reported no details of the procedure used. In a third of these (n = 11), it was not possible to infer the approach used from references cited or software used. The nature of the imputation model was rarely reported. MI was frequently used as a secondary analysis (n = 40) either to justify reporting a simpler approach or as a form of sensitivity analysis.

Conclusions: Whilst still relatively uncommon, the use of MI has risen substantially, particularly in trials. MI is rarely adequately reported, leading to doubt about its appropriateness in some cases. This gives rise to uncertainty about conclusions reached and poses a barrier to attempts to replicate analyses. Guidelines for the reporting of MI should be developed.