Comparison of Random Forest and Parametric Imputation Models for Imputing Missing Data Using MICE: A CALIBER Study

Multivariate imputation by chained equations (MICE) is commonly used for imputing missing data in epidemiologic research. The “true” imputation model may contain nonlinearities which are not included in default imputation models. Random forest imputation is a machine learning technique which can acc...

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Detalles Bibliográficos
Autores principales: Shah, Anoop D., Bartlett, Jonathan W., Carpenter, James, Nicholas, Owen, Hemingway, Harry
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Practice of Epidemiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3939843/
https://www.ncbi.nlm.nih.gov/pubmed/24589914
http://dx.doi.org/10.1093/aje/kwt312

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3939843/
https://www.ncbi.nlm.nih.gov/pubmed/24589914
http://dx.doi.org/10.1093/aje/kwt312

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