Joint modelling of longitudinal and time-to-event data with application to predicting abdominal aortic aneurysm growth and rupture

Shared random effects joint models are becoming increasingly popular for investigating the relationship between longitudinal and time-to-event data. Although appealing, such complex models are computationally intensive, and quick, approximate methods may provide a reasonable alternative. In this pap...

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Detalles Bibliográficos
Autores principales: Sweeting, Michael J, Thompson, Simon G
Formato: Online Artículo Texto
Lenguaje:English
Publicado: WILEY-VCH Verlag 2011
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3443386/
https://www.ncbi.nlm.nih.gov/pubmed/21834127
http://dx.doi.org/10.1002/bimj.201100052

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3443386/
https://www.ncbi.nlm.nih.gov/pubmed/21834127
http://dx.doi.org/10.1002/bimj.201100052

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