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Evaluation of Multiple Imputation with Large Proportions of Missing Data: How Much Is Too Much?
BACKGROUND: Multiple Imputation (MI) is known as an effective method for handling missing data in public health research. However, it is not clear that the method will be effective when the data contain a high percentage of missing observations on a variable. METHODS: Using data from “Predictive Stu...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Tehran University of Medical Sciences
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8426774/ https://www.ncbi.nlm.nih.gov/pubmed/34568175 http://dx.doi.org/10.18502/ijph.v50i7.6626 |