The proportion of missing data should not be used to guide decisions on multiple imputation

OBJECTIVES: Researchers are concerned whether multiple imputation (MI) or complete case analysis should be used when a large proportion of data are missing. We aimed to provide guidance for drawing conclusions from data with a large proportion of missingness. STUDY DESIGN AND SETTING: Via simulation...

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Detalles Bibliográficos
Autores principales: Madley-Dowd, Paul, Hughes, Rachael, Tilling, Kate, Heron, Jon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6547017/
https://www.ncbi.nlm.nih.gov/pubmed/30878639
http://dx.doi.org/10.1016/j.jclinepi.2019.02.016

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6547017/
https://www.ncbi.nlm.nih.gov/pubmed/30878639
http://dx.doi.org/10.1016/j.jclinepi.2019.02.016

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