Multiple imputation of missing data under missing at random: compatible imputation models are not sufficient to avoid bias if they are mis-specified

OBJECTIVES: Epidemiological studies often have missing data, which are commonly handled by multiple imputation (MI). Standard (default) MI procedures use simple linear covariate functions in the imputation model. We examine the bias that may be caused by acceptance of this default option and evaluat...

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Detalhes bibliográficos
Publicado no:J Clin Epidemiol
Main Authors: Curnow, Elinor, Carpenter, James R., Heron, Jon E., Cornish, Rosie P., Rach, Stefan, Didelez, Vanessa, Langeheine, Malte, Tilling, Kate
Formato: Artigo
Idioma:Inglês
Publicado em: 2023
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7615471/
https://ncbi.nlm.nih.gov/pubmed/37343895
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.jclinepi.2023.06.011
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