Abstract
The authors attempted to catalog the use of procedures to impute missing data in the epidemiologic literature and to determine the degree to which imputed results differed in practice from unimputed results. The full text of articles published in 2005 and 2006 in four leading epidemiologic journals was searched for the text imput. Sixteen articles utilizing multiple imputation, inverse probability weighting, or the expectation-maximization algorithm to impute missing data were found. The small number of relevant manuscripts and diversity of detail provided precluded systematic analysis of the use of imputation procedures. To form a bridge between current and future practice, the authors suggest details that should be included in articles that utilize these procedures.
Keywords
Imputation (statistics)Missing dataInverse probability weightingWeightingStatisticsComputer scienceMedicineInformation retrievalMathematicsEstimator
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Publication Info
- Year
- 2008
- Type
- review
- Volume
- 168
- Issue
- 4
- Pages
- 355-357
- Citations
- 229
- Access
- Closed
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Cite This
Mark A. Klebanoff,
Stephen R. Cole
(2008).
Use of Multiple Imputation in the Epidemiologic Literature.
American Journal of Epidemiology
, 168
(4)
, 355-357.
https://doi.org/10.1093/aje/kwn071
Identifiers
- DOI
- 10.1093/aje/kwn071