Assumptions and analysis planning in studies with missing data in multiple variables: moving beyond the MCAR/MAR/MNAR classification

Researchers faced with incomplete data are encouraged to consider whether their data are ‘missing completely at random’ (MCAR), ‘missing at random’ (MAR) or ‘missing not at random’ (MNAR) when planning their analysis. However, there are two major problems with this classification as originally defin...

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Detalles Bibliográficos
Autores principales: Lee, Katherine J, Carlin, John B, Simpson, Julie A, Moreno-Betancur, Margarita
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Education Corner
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10396404/
https://www.ncbi.nlm.nih.gov/pubmed/36779333
http://dx.doi.org/10.1093/ije/dyad008

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10396404/
https://www.ncbi.nlm.nih.gov/pubmed/36779333
http://dx.doi.org/10.1093/ije/dyad008

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