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Accounting for missing data in statistical analyses: multiple imputation is not always the answer
BACKGROUND: Missing data are unavoidable in epidemiological research, potentially leading to bias and loss of precision. Multiple imputation (MI) is widely advocated as an improvement over complete case analysis (CCA). However, contrary to widespread belief, CCA is preferable to MI in some situation...
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| Publicado no: | Int J Epidemiol |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6693809/ https://ncbi.nlm.nih.gov/pubmed/30879056 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/ije/dyz032 |
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