What difference does multiple imputation make in longitudinal modeling of EQ-5D-5L data? Empirical analyses of simulated and observed missing data patterns

PURPOSE: Although multiple imputation is the state-of-the-art method for managing missing data, mixed models without multiple imputation may be equally valid for longitudinal data. Additionally, it is not clear whether missing values in multi-item instruments should be imputed at item or score-level...

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Detalles Bibliográficos
Autores principales: Rösel, Inka, Serna-Higuita, Lina María, Al Sayah, Fatima, Buchholz, Maresa, Buchholz, Ines, Kohlmann, Thomas, Martus, Peter, Feng, You-Shan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9023409/
https://www.ncbi.nlm.nih.gov/pubmed/34797507
http://dx.doi.org/10.1007/s11136-021-03037-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9023409/
https://www.ncbi.nlm.nih.gov/pubmed/34797507
http://dx.doi.org/10.1007/s11136-021-03037-3

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