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Effects of Different Missing Data Imputation Techniques on the Performance of Undiagnosed Diabetes Risk Prediction Models in a Mixed-Ancestry Population of South Africa

BACKGROUND: Imputation techniques used to handle missing data are based on the principle of replacement. It is widely advocated that multiple imputation is superior to other imputation methods, however studies have suggested that simple methods for filling missing data can be just as accurate as com...

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Detalles Bibliográficos
Autores principales: Masconi, Katya L., Matsha, Tandi E., Erasmus, Rajiv T., Kengne, Andre P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4583496/
https://www.ncbi.nlm.nih.gov/pubmed/26406594
http://dx.doi.org/10.1371/journal.pone.0139210