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Penalization and shrinkage methods produced unreliable clinical prediction models especially when sample size was small
OBJECTIVES: When developing a clinical prediction model, penalization techniques are recommended to address overfitting, as they shrink predictor effect estimates toward the null and reduce mean-square prediction error in new individuals. However, shrinkage and penalty terms (‘tuning parameters’) ar...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8026952/ https://www.ncbi.nlm.nih.gov/pubmed/33307188 http://dx.doi.org/10.1016/j.jclinepi.2020.12.005 |