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Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls

Jonathan A C Sterne; Ian R. White; John B. Carlin; Michael Spratt; Patrick Royston; Michael G. Kenward; Angela Wood; James R. Carpenter · BMJ · 2009

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Author / responsible party
Jonathan A C Sterne; Ian R. White; John B. Carlin; Michael Spratt; Patrick Royston; Michael G. Kenward; Angela Wood; James R. Carpenter
Publisher
BMJ
Year
2009
Language
English

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Summary

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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

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APA 7

Sterne, J. A. C, White, I. R, Carlin, J. B, Spratt, M, Royston, P, Kenward, M. G, Wood, A, & Carpenter, J. R. (2009). Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. https://doi.org/10.1136/bmj.b2393

MLA

Sterne, Jonathan A C, et al. "Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls." 2009. https://doi.org/10.1136/bmj.b2393.

Chicago

Sterne, Jonathan A C, Ian R. White, John B. Carlin, Michael Spratt, Patrick Royston, Michael G. Kenward, Angela Wood, and James R. Carpenter. 2009. "Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls.". https://doi.org/10.1136/bmj.b2393.

Harvard

Sterne, J. A. C. et al. 2009, Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls, BMJ, available at: https://doi.org/10.1136/bmj.b2393 [Accessed 7 Aug. 2026].

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Title
Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls
Author / contributors
Jonathan A C Sterne; Ian R. White; John B. Carlin; Michael Spratt; Patrick Royston; Michael G. Kenward; Angela Wood; James R. Carpenter
Publisher
BMJ
Publication year
2009
Language
English

Subjects

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Imputation (statistics); Missing data; Computer science; Data science; Data mining; Statistics; Econometrics; Mathematics; Machine learning
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