title: Bayesian joint modeling of longitudinal and spatial survival AIDS data.
abstract: Joint analysis of longitudinal and survival data has received increasing attention in the recent years, especially for analyzing cancer and AIDS data. As both repeated measurements (longitudinal) and time-to-event (survival) outcomes are observed in an individual, a joint modeling is more appropriate because it takes into account the dependence between the two types of responses, which are often analyzed separately. We propose a Bayesian hierarchical model for jointly modeling longitudinal and survival data considering functional time and spatial frailty effects, respectively. That is, the proposed model deals with non-linear longitudinal effects and spatial survival effects accounting for the unobserved heterogeneity among individuals living in the same region. This joint approach is applied to a cohort study of patients with HIV/AIDS in Brazil during the years 2002-2006. Our Bayesian joint model presents considerable improvements in the estimation of survival times of the Brazilian HIV/AIDS patients when compared with those obtained through a separate survival model and shows that the spatial risk of death is the same across the different Brazilian states. Copyright © 2016 John Wiley & Sons, Ltd.
authors.affiliation: Centro de Investigação Interdisciplinar Egas Moniz (ciiEM), Escola Superior de Saúde Egas Moniz, Quinta da Granja, Monte de Caparica, Caparica, 2829-511, Portugal.
authors.forename: Rui
authors.identifier: 0000-0003-1862-7066
authors.initials: R
authors.lastname: Martins
authors.affiliation: Centro de Estatística e Aplicações da Universidade de Lisboa (CEAUL), Bloco C6, Piso 4Campo Grande, Lisbon, 1749-016, Portugal.|Departamento de Matemática, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1, Lisbon, 1049-001, Portugal.
authors.forename: Giovani L
authors.initials: GL
authors.lastname: Silva
authors.affiliation: Centro de Estatística e Aplicações da Universidade de Lisboa (CEAUL), Bloco C6, Piso 4Campo Grande, Lisbon, 1749-016, Portugal.|Faculdade de Ciências Médicas da Universidade Nova de Lisboa, Campo Mártires da Pátria, 130, Lisbon, 1169-056, Portugal.
authors.forename: Valeska
authors.initials: V
authors.lastname: Andreozzi
mesh_terms: D000163:Acquired Immunodeficiency Syndrome / Q000401:mortality*; D001499:Bayes Theorem; D001938:Brazil / Q000453:epidemiology; D006801:Humans; D008137:Longitudinal Studies; D015233:Models, Statistical
keywords: Bayesian analysis; joint model; repeated measurements; spatial frailty; time-to-event data