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...

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Detalles Bibliográficos
Autores principales: Riley, Richard D., Snell, Kym I.E., Martin, Glen P., Whittle, Rebecca, Archer, Lucinda, Sperrin, Matthew, Collins, Gary S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Original Article
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

Internet

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

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