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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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| Publicat a: | PLoS One |
|---|---|
| Autors principals: | , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Public Library of Science
2015
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4583496/ https://ncbi.nlm.nih.gov/pubmed/26406594 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0139210 |
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