Research
Peer-Reviewed Journal Articles
2024
Chen, S.; Alvares, D.; Jackson, C.; Barrett, J.: Bayesian blockwise inference for joint models of longitudinal and multistate processes. [arXiv]
Alvares, D.; van Niekerk, J.; Krainski, E.T.; Rue, H.; Rustand, D.: Bayesian survival analysis with INLA. [arXiv]
Vicuña, L.; Barrientos, E.; Leiva-Yamaguchi, V.; Alvares, D.; Mericq, V.; Pereira, A.; Eyheramendy, S.: Joint models reveal genetic architecture of transitions between pubertal stages and their association with BMI in a Latino population. [medRxiv]
2023
Pérez-Jeldres, T.; Magne, F.; Ascui, G.; Alvares, D.; Orellana, M.; Álvarez-Lobos, M.; Hernández-Rocha, C.; Azocar, L.; Aguilar, N.; Espino, A.; Estela, R.; Escobar, S.; Zazueta, A.; Baéz, P.; Silva, V.; De la Vega, A.; Arriagada, E.; Pavez-Ovalle, C.; Diaz-Asencio, A.; Travisany, D.; Miquel, J.F.; Villablanca, E.J.; Kronenberg, M.; Bustamante; M.L.: Amerindian ancestry proportion as a risk factor for inflammatory bowel diseases: results from a Latin American Andean cohort. Frontiers in Medicine, 10, 1-12, 2023. [DOI]
Alvares, D.; Leiva-Yamaguchi, V.: A two-stage approach for Bayesian joint models: Reducing complexity while maintaining accuracy. Statistics and Computing, 33(5), 1-11, 2023. [DOI]
López, F.; Contreras, M.; Nussbaum, M.; Paredes, R.; Gelerstein, D.; Alvares, D.; Chiuminatto, P.: Developing critical thinking in technical and vocational education and training. Education Sciences, 13(6), 1-21, 2023. [DOI]
Gutiérrez, I.; Gutiérrez, L.; Alvares, D.: A new flexible Bayesian hypothesis test for multivariate data. Statistics and Computing, 33(2), 1-16, 2023. [DOI]
Vicuña, L.; Barrientos, E.; Norambuena, T.; Alvares, D.; Gana, J.C.; Leiva-Yamaguchi, V.; Meza, C.; Santos, J.L.; Mericq, V.; Pereira, A.; Eyheramendy, S.: New insights from GWAS on BMI-related growth phenotypes in a longitudinal cohort of admixed children with Native American and European ancestry. iScience, 26(2), 1-16, 2023. [DOI]
2022
Gutiérrez, I.; Gutiérrez, L.; Alvares, D.: A Bayesian nonparametric test for cross-group differences relative to a control. New Frontiers in Bayesian Statistics: BAYSM 2021, Springer Proceedings in Mathematics & Statistics, 405, 79-89, 2022. [DOI]
Pérez-Jeldres, T.; Pizarro, B.; Ascui, G.; Orellana, M.; Cerda-Villablanca, M.; Alvares, D.; De la Vega, A.; Canistra, M.; Cornejo, B.; Baéz, P.; Silva, V.; Arriagada, E.; Rivera-Nieves, J.; Estela, R.; Hernández-Rocha, C.; Álvarez-Lobos, M.; Tobar, F.: Ethnicity influences phenotype and clinical outcomes: comparing a South American with a North American inflammatory bowel disease cohort. Medicine, 101(36), 1-12, 2022. [DOI]
Cortázar, C.; Nussbaum, M.; Alario-Hoyos, C.; Goñi, J.; Alvares, D.: The impacts of scaffolding socially shared regulation on teamwork in an online project-based course. The Internet and Higher Education, 55, 1-22, 2022. [DOI]
Reveco-Quiroz, P.; Sandoval-Díaz; J.; Alvares, D.: Bayesian modeling for pro-environmental behavior data: sorting and selecting relevant variables. Stochastic Environmental Research and Risk Assessment, 36, 3961-3977, 2022. [DOI]
Rubio, F.J.; Alvares, D.; Redondo-Sánchez, D.; Marcos-Gragera, R.; Sánchez, M.J.; Luque-Fernández, M.A.: Bayesian variable selection and survival modeling: assessing the most important comorbidities that impact lung and colorectal cancer survival in Spain. BMC Medical Research Methodology, 22(95), 1-14, 2022. [DOI]
Rojas, M.; Nussbaum, M.; Guerrero, O.; Chiuminatto, P.; Greiff, S.; Del Rio, R.; Alvares, D.: Integrating collaborative script and group awareness to support group regulation and emotions towards collaborative problem solving. International Journal of Computer-Supported Collaborative Learning, 17, 135-168, 2022. [DOI]
Rodríguez, M.F.; Nussbaum, M.; Yunis, L.; Reyes, T.; Alvares, D.; Joublan, J.; Navarrete, P.: Using scaffolded feedforward and peer feedback to improve problem-based learning in large classes. Computers & Education, 182, 1-13, 2022. [DOI]
2021
Beserra, V.; Nussbaum, M.; Navarrete, M.; Alvares, D.: Teaching through dance: an opportunity to introduce physically active academic lessons. Teaching and Teacher Education, 106, 1-13, 2021. [DOI]
Alvares, D.; Rubio, F.J.: A tractable Bayesian joint model for longitudinal and survival data. Statistics in Medicine, 40(19), 4213-4229, 2021. [DOI]
Alvares, D.; Paredes, F.; Vargas, C.; Ferreccio, C.: A strategy to impute age at onset of a particular condition from external sources. Statistical Methods in Medical Research, 30(8), 1771-1781, 2021. [DOI]
Cortázar, C.; Nussbaum, M.; Harcha, J.; Alvares, D.; López, F.; Goñi, J.; Cabezas, V.: Promoting critical thinking in an online, project-based course. Computers in Human Behavior, 119, 1-18, 2021. [DOI]
Alvares, D.; Lázaro, E.; Gómez‐Rubio, V.; Armero, C.: Bayesian survival analysis with BUGS. Statistics in Medicine, 40(12), 2975-3020, 2021. [DOI]
Reis, H.M.; Alvares, D.; Jaques, P.A.; Isotani, S.: A proposal of model of emotional regulation in intelligent learning environments. Informatics in Education, 20(2), 317-332, 2021. [DOI]
Alvares, D.; Armero, C.; Forte, A.; Chopin, N.: Sequential Monte Carlo methods in Bayesian joint models for longitudinal and time-to-event data. Statistical Modelling, 21(1-2), 161-181, 2021. [DOI]
Reis, H.M.; Alvares, D.; Jaques, P.A.; Isotani, S.: Customization of emotional regulation according to the personality of students in intelligent tutoring systems. Brazilian Journal of Computers in Education, 29, 48-72, 2021. [DOI]
Araneda, D.; Galarce, J.; Alvares, D.; Nussbaum, M.: What to learn? Socialization of the subject hierarchy in schools. Educational Studies, 57(1), 58-77, 2021. [DOI]
Lázaro, E.; Armero, C.; Alvares, D.: Bayesian regularization for flexible baseline hazard functions in Cox survival models. Biometrical Journal, 63(1), 7-26, 2021. [DOI]
Leiva-Yamaguchi, V.; Alvares, D.: A two-stage approach for Bayesian joint models of longitudinal and survival data: correcting bias with informative prior. Entropy, 23(1), 1-10, 2021. [DOI]
2020
Goñi, J.; Cortázar, C.; Alvares, D.; Donoso, U.; Miranda, C.: Is teamwork different online versus face-to-face? A case in Engineering education. Sustainability, 12(24), 1-18, 2020. [DOI]
Chamorro, C.; Alvares, D.; Berger, S.; Balocci, F.; Rodriguez, X.; Soza, F.: Psychometric properties of the Chilean version of the Quick Disabilities of the Arm, Shoulder and Hand (Quick DASH) questionnaire for patients with shoulder disorders. Archivos de Medicina del Deporte, 37(5), 305-309, 2020. [DOI]
Oliveira, C.M.; Tureck, L.V.; Alvares, D.; Liu, C.; Horimoto, A.R.V.R.; Balcells, M.; Alvim, R.O.; Krieger, J.E.; Pereira, A.C.: Relationship between marital status and incidence of type 2 diabetes mellitus in a Brazilian rural population: the Baependi Heart Study. PLOS ONE, 15(8), 1-10, 2020. [DOI]
Ovalle, C.; Alvares, D.: A Bayesian graphical and probabilistic proposal for bias analysis. Quantitative Psychology: IMPS 2019, Springer International Publishing, 322, 69-78, 2020. [DOI]
Vieira, C.L.Z.; Garshick, E.; Alvares, D.; Schwartz, J.; Huang, S.; Vokonas, P.; Gold, D.R.; Koutrakis, P.: Association between ambient beta particle radioactivity and lower hemoglobin concentrations in a cohort of elderly men. Environment International, 139, 1-7, 2020. [DOI]
Pavani, J.; Alvares, D.: Statistically validating patient self-reporting questionnaires in medicine. SAGE Research Methods Cases: Medicine and Health, 1-19, 2020. [DOI]
Oliveira, C.M.; Tureck, L.V.; Alvares, D.; Liu, C.; Horimoto, A.R.V.R.; Alvim, R.O.; Krieger, J.E.; Pereira, A.C.: Cardiometabolic risk factors correlated with the incidence of dysglycaemia in a Brazilian normoglycaemic sample: the Baependi Heart Study cohort. Diabetology & Metabolic Syndrome, 12(6), 1-7, 2020. [DOI]
2019
Alvares, D.; Haneuse, S.; Lee, C.; Lee, K.H.: SemiCompRisks: an R package for the analysis of independent and cluster-correlated semi-competing risks data. The R Journal, 11(1), 376-400, 2019. [DOI]
Vieira, C.L.Z.; Alvares, D.; Blomberg, A.; Schwartz, J.; Coull, B.; Huang, S.; Koutrakis, P.: Geomagnetic disturbances driven by solar activity enhance total and cardiovascular mortality risk in 263 U.S. cities. Environmental Health, 18(83), 1-10, 2019. [DOI]
2018
Reis, H.M.; Alvares, D.; Jaques, P.A.; Isotani, S.: Analysis of permanence time in emotional states: a case study using educational software. Intelligent Tutoring Systems, Springer International Publishing, 180-190, 2018. [DOI]
Cacheiro, P.; Lorenzo-Arribas, A.; Lázaro, E.; Alvares, D.; Barrio, I.; Bofill Roig, M.; Branco, M.; Gómez-Mateu, M.; Vilor-Tejedor, N.; Pérez-Haro, M.J.: Reproducibility, visibility and diversity: current trends in Biostatistics viewed by young researchers. Boletín de Estadística e Investigación Operativa, 40(1), 73-91, 2018. [ISSN]
Alvares, D.; Armero, C.; Forte, A.: What does objective mean in a Dirichlet-multinomial framework? International Statistical Review, 86(1), 106-118, 2018. [DOI]
Isotani, S.; Reis, H.M.; Alvares, D.; Brandão, A.A.F.; Brandão, L.O.: A DGS gesture dictionary for modelling on mobile devices. Interactive Learning Environments, 26(3), 320-336, 2018. [DOI]
2017
Rué, M.; Andrinopoulou, E.R.; Alvares, D.; Armero, C.; Forte, A.; Blanch, L.: 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, 2017. [DOI]
Alvares, D.; Armero, C.; Forte, A.; Serra, J.; Galipienso, L.; Rubio, L.: Incidence and control of black spot syndrome of tiger nut. Annals of Applied Biology, 171(3), 417-423, 2017. [DOI]
Sanz-Puig, M.; Lázaro, E.; Armero, C.; Alvares, D.; Martínez, A.; Rodrigo, D.: S. Typhimurium virulence changes caused by exposure to different non-thermal preservation treatments using C. elegans as a model organism. International Journal of Food Microbiology, 262, 49-54, 2017. [DOI]
Alvares, D.; Armero, C.; Forte, A.; Chopin, N.: Sequential Monte Carlo methods in random intercept models for longitudinal data. Bayesian Statistics in Action: BAYSM 2016, Springer Proceedings in Mathematics & Statistics, 194, 3-9, 2017. [DOI]
2016
Alvares, D.; Armero, C.; Forte, A.; Rubio, L.: Exploring Bayesian models to evaluate control procedures for plant disease. Statistics and Operations Research Transactions, 40(1), 139-152, 2016. [DOI]