Handling missing predictor values when validating and applying a prediction model to new patients

Missing data present challenges for development and real‐world application of clinical prediction models. While these challenges have received considerable attention in the development setting, there is only sparse research on the handling of missing data in applied settings. The main unique feature...

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Detalles Bibliográficos
Autores principales: Hoogland, Jeroen, van Barreveld, Marit, Debray, Thomas P. A., Reitsma, Johannes B., Verstraelen, Tom E., Dijkgraaf, Marcel G. W., Zwinderman, Aeilko H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2020
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7586995/
https://www.ncbi.nlm.nih.gov/pubmed/32687233
http://dx.doi.org/10.1002/sim.8682

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7586995/
https://www.ncbi.nlm.nih.gov/pubmed/32687233
http://dx.doi.org/10.1002/sim.8682

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