Accommodating heterogeneous missing data patterns for prostate cancer risk prediction

BACKGROUND: We compared six commonly used logistic regression methods for accommodating missing risk factor data from multiple heterogeneous cohorts, in which some cohorts do not collect some risk factors at all, and developed an online risk prediction tool that accommodates missing risk factors fro...

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Detalles Bibliográficos
Autores principales: Neumair, Matthias, Kattan, Michael W., Freedland, Stephen J., Haese, Alexander, Guerrios-Rivera, Lourdes, De Hoedt, Amanda M., Liss, Michael A., Leach, Robin J., Boorjian, Stephen A., Cooperberg, Matthew R., Poyet, Cedric, Saba, Karim, Herkommer, Kathleen, Meissner, Valentin H., Vickers, Andrew J., Ankerst, Donna P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9306143/
https://www.ncbi.nlm.nih.gov/pubmed/35864460
http://dx.doi.org/10.1186/s12874-022-01674-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9306143/
https://www.ncbi.nlm.nih.gov/pubmed/35864460
http://dx.doi.org/10.1186/s12874-022-01674-x

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