Bibliographic citations
Chiroque, P., Pamela (2018). Joint modeling of longitudinal markers and survival data: an approach via dynamic hierarchical models [Universidade Federal do Rio de Janeiro]. http://renati.sunedu.gob.pe/handle/sunedu/1596717
Chiroque, P., Pamela Joint modeling of longitudinal markers and survival data: an approach via dynamic hierarchical models []. BR: Universidade Federal do Rio de Janeiro; 2018. http://renati.sunedu.gob.pe/handle/sunedu/1596717
@phdthesis{renati/2105,
title = "Joint modeling of longitudinal markers and survival data: an approach via dynamic hierarchical models",
author = "Pamela M. Chiroque-Solano",
publisher = "Universidade Federal do Rio de Janeiro",
year = "2018"
}
Models for longitudinal and time-to-event data are proposed in the context of joint modeling. Three alternative regression models for the longitudinal data are presented with time evolution based on Generalized Hierarchical Dynamic Linear Model. These regression models are standard, quantile and Markov switching regression. For the survival baseline hazard function some parametric and semi-parametric forms are used and validated through simulated results. Some dependence relations are explored for the semiparametric function. In all proposals, the link between the two sub-models is a exible choice which is discussed. Inference procedure is developed under the Bayesian approach. Comparison metrics are adapted and used for model validation alongside standard metrics. Four data sets are used to illustrate the proposed methodologies.
File | Description | Size | Format | |
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ChiroqueSolanoPM.pdf | Tesis | 7.55 MB | Adobe PDF | View/Open |
Autorizacion.pdf Restricted Access | Autorización del registro | 166.22 kB | Adobe PDF | View/Open Request a copy |
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