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The effect of high prevalence of missing data on estimation of the coefficients of a logistic regression model when using multiple imputation
BACKGROUND: Multiple imputation is frequently used to address missing data when conducting statistical analyses. There is a paucity of research into the performance of multiple imputation when the prevalence of missing data is very high. Our objective was to assess the performance of multiple imputa...
Autores principales: | Austin, Peter C., van Buuren, Stef |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9290209/ https://www.ncbi.nlm.nih.gov/pubmed/35850734 http://dx.doi.org/10.1186/s12874-022-01671-0 |
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