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

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

Abstract 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...

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Bibliographic Details
Main Authors: Solène Desmée, France Mentré, Christine Veyrat-Follet, Bernard Sébastien, Jérémie Guedj
Format: Article
Language:English
Published: BMC 2017-07-01
Series:BMC Medical Research Methodology
Subjects:
Calibration
Discrimination
Hamiltonian Monte Carlo
Individual dynamic prediction
Nonlinear joint model
Online Access:http://link.springer.com/article/10.1186/s12874-017-0382-9

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http://link.springer.com/article/10.1186/s12874-017-0382-9

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