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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2015
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| Materias: | |
| 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 |