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A Bayesian nonlinear mixed-effects disease progression model

A nonlinear mixed-effects approach is developed for disease progression models that incorporate variation in age in a Bayesian framework. We further generalize the probability model for sensitivity to depend on age at diagnosis, time spent in the preclinical state and sojourn time. The developed mod...

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Détails bibliographiques
Publié dans:J Biom Biostat
Auteurs principaux: Kim, Seongho, Jang, Hyejeong, Wu, Dongfeng, Abrams, Judith
Format: Artigo
Langue:Inglês
Publié: 2015
Sujets:
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC4718583/
https://ncbi.nlm.nih.gov/pubmed/26798562
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.4172/2155-6180.1000271
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