Nonlinear joint models for individual dynamic prediction of risk of death using Hamiltonian Monte Carlo: application to metastatic prostate cancer

BACKGROUND: Joint models of longitudinal and time-to-event data are increasingly used to perform individual dynamic prediction of a risk of event. However the difficulty to perform inference in nonlinear models and to calculate the distribution of individual parameters has long limited this approach...

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Detalles Bibliográficos
Autores principales: Desmée, Solène, Mentré, France, Veyrat-Follet, Christine, Sébastien, Bernard, Guedj, Jérémie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5513366/
https://www.ncbi.nlm.nih.gov/pubmed/28716060
http://dx.doi.org/10.1186/s12874-017-0382-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5513366/
https://www.ncbi.nlm.nih.gov/pubmed/28716060
http://dx.doi.org/10.1186/s12874-017-0382-9

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