Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls
University of Bristol · Institute of Infection and Immunity · +6 more institutions
Indexed incrossrefpubmed
Abstract
Most studies have some missing data. Jonathan Sterne and colleagues describe the appropriate use and reporting of the multiple imputation approach to dealing with them
Citation impact
7,107
total citations
- FWCI
- 108.14
- Percentile
- 100%
- References
- 30
Citations per year
Authors
8- JAJonathan A C SterneCorresponding
University of Bristol, Institute of Infection and Immunity
- IRIan R. White
MRC Biostatistics Unit, University of Bristol
- JBJohn B. Carlin
Murdoch Children's Research Institute, University of Melbourne
- MSMichael Spratt
University of Bristol
- PRPatrick Royston
MRC Clinical Trials Unit at UCL
Topics & keywords
Topics
Keywords
- Imputation (statistics)
- Missing data
- Computer science
- Data science
- Data mining
- Statistics
- Econometrics
- Mathematics
UN Sustainable Development Goals
- Good health and well-being
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