Variable Importance and Prediction Methods for Longitudinal Problems with Missing Variables

We present prediction and variable importance (VIM) methods for longitudinal data sets containing continuous and binary exposures subject to missingness. We demonstrate the use of these methods for prognosis of medical outcomes of severe trauma patients, a field in which current medical practice inv...

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Detalles Bibliográficos
Autores principales: Díaz, Iván, Hubbard, Alan, Decker, Anna, Cohen, Mitchell
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4376910/
https://www.ncbi.nlm.nih.gov/pubmed/25815719
http://dx.doi.org/10.1371/journal.pone.0120031

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4376910/
https://www.ncbi.nlm.nih.gov/pubmed/25815719
http://dx.doi.org/10.1371/journal.pone.0120031

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