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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Enregistré dans:
Détails bibliographiques
Publié dans:Am J Epidemiol
Auteurs principaux: Moreno-Betancur, Margarita, Lee, Katherine J, Leacy, Finbarr P, White, Ian R, Simpson, Julie A, Carlin, John B
Format: Artigo
Langue:Inglês
Publié: Oxford University Press 2018
Sujets:
Practice of Epidemiology
Accès en ligne: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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