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...
| Publicado en: | BMC Medical Research Methodology Vol. 17; pp. 1 - 13 |
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| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
BioMed Central
7/17/2017
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| Acceso en línea: | Ver este registro en EBSCOhost |