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Editorial
. 2015 Feb;41(2):348-50.
doi: 10.1007/s00134-014-3624-x. Epub 2015 Jan 13.

Multiple imputation: a mature approach to dealing with missing data

S Chevret  1 , S Seaman, M Resche-Rigon
Affiliations
Editorial

Multiple imputation: a mature approach to dealing with missing data

S Chevret et al. Intensive Care Med. 2015 Feb.
No abstract available

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Conflict of interest statement

Conflicts of interest None.

Figures

Fig. 1
Fig. 1
Scheme of the main steps in multiple imputation. Rubin’s rules give overall estimates and corresponding standard errors from the m separate analyses [5]
See this image and copyright information in PMC

References

    1. Eekhout I, de Boer RM, Twisk JW, de Vet HC, Heymans MW. Missing data: a systematic review of how they are reported and handled. Epidemiology. 2012;23(5):729–732. - PubMed
    1. Vesin A, Azoulay E, Ruckly S, Vignoud L, Rusinova K, Benoit D, Soares M, Azeivedo-Maia P, Abroug F, Benbenishty J, Timsit JF. Reporting and handling missing values in clinical studies in intensive care units. Intensive Care Med. 2013;39:1396–1404. - PubMed
    1. Lee CH, Arzeno NM, Ho JC, Vikalo H, Ghosh J. A imputation-enhanced algorithm for ICU mortality prediction. Comput Cardiol. 2012;39:253–256.
    1. Rubin DB. Inference and missing data. Biometrika. 1976;63:581–592.
    1. Rubin DB. Multiple imputation for nonresponse in surveys. John Wiley; New York: 1987.

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