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Penalized logistic regression with low prevalence exposures beyond high dimensional settings
Estimating and selecting risk factors with extremely low prevalences of exposure for a binary outcome is a challenge because classical standard techniques, markedly logistic regression, often fail to provide meaningful results in such settings. While penalized regression methods are widely used in h...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6527211/ https://www.ncbi.nlm.nih.gov/pubmed/31107924 http://dx.doi.org/10.1371/journal.pone.0217057 |