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Canonical Causal Diagrams to Guide the Treatment of Missing Data in Epidemiologic Studies
With incomplete data, the “missing at random” (MAR) assumption is widely understood to enable unbiased estimation with appropriate methods. While the need to assess the plausibility of MAR and to perform sensitivity analyses considering “missing not at random” (MNAR) scenarios has been emphasized, t...
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| Publicado no: | Am J Epidemiol |
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| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6269242/ https://ncbi.nlm.nih.gov/pubmed/30124749 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/aje/kwy173 |
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