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Bring More Data!—A Good Advice? Removing Separation in Logistic Regression by Increasing Sample Size
The parameters of logistic regression models are usually obtained by the method of maximum likelihood (ML). However, in analyses of small data sets or data sets with unbalanced outcomes or exposures, ML parameter estimates may not exist. This situation has been termed ‘separation’ as the two outcome...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2019
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6926877/ https://www.ncbi.nlm.nih.gov/pubmed/31766753 http://dx.doi.org/10.3390/ijerph16234658 |