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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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| Publicat a: | J Clin Epidemiol |
|---|---|
| Autors principals: | , , , , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2023
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| Matèries: | |
| Accés en línia: | 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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