Multiple Imputation for General Missing Data Patterns in the Presence of High-dimensional Data

Multiple imputation (MI) has been widely used for handling missing data in biomedical research. In the presence of high-dimensional data, regularized regression has been used as a natural strategy for building imputation models, but limited research has been conducted for handling general missing da...

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Detalles Bibliográficos
Autores principales: Deng, Yi, Chang, Changgee, Ido, Moges Seyoum, Long, Qi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4751511/
https://www.ncbi.nlm.nih.gov/pubmed/26868061
http://dx.doi.org/10.1038/srep21689

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4751511/
https://www.ncbi.nlm.nih.gov/pubmed/26868061
http://dx.doi.org/10.1038/srep21689

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