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Departament d’Estadística i Investigació Operativa Universitat de València, Spain
RESEARCH INTEREST Bayesian hierarchical models; Bayesian survival analysis; Longitudinal data; Joint models of longitudinal and survival data; Hidden Markov models.
RECENT PAPERS . C. Armero, S. Cabras, M.E. Castellanos, S. Perra, A. Quirós, M.J. Oruezábal and J. Sánchez-Rubio (2016). Bayesian analysis of a disability model for lung cancer survival. Statistical Methods in Medical Research, 25(1): 336-351. . C. Armero, C. Forné, M. Rué, A. Forte, H. Perpiñán, G. Gómez-Melis, and M. Baré (2016). Bayesian joint ordinal and survival modeling for breast cáncer risk assessment. Statistics in Medicine, 35(28):5267-5282. . M. Rué, R. Andrinopoulou, D. Alvares, C. Armero, A. Forte, and Ll. Blanch (2017). Bayesian joint modeling of bivariate longitudinal and competing risks data: An application to study patient-ventilator asynchronies in critical care patients. Biometrical Journal, 59(6):1184-1203. . D. Alvares, C. Armero, and A. Forte (2018) What does objective mean in a Dirichlet-multinomial framework? International Statistical Review, 86(1):106-118. . C. Armero, A. Forte, H. Perpiñán, M.J. Sanahuja and S. Agustí (2018) Bayesian joint modeling for assessing the progression of Chronic Kidney Disease in children. Statistical Methods in Medical Research, 27(1):298-311. . C. Armero, S. Cabras, M.E. Castellanos, and A. Quirós (2018). Two-stage Bayesian approach for GWAS with known genealogy. Journal of Computational and Graphical Statistics, DOI: 10.1080/10618600.2018.1483828. . E. Lázaro, C. Armero, and V. Gómez-Rubio (2018). Approximate Bayesian inference for mixture cure models. arXiv preprint arXiv:1806.09362
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