Publications

Articles submitted

  • Zhang, Z., Inacio, V. and de Carvalho, M. (2025+). The underlap coefficient as a measure of \a biomarker’s discriminatory ability. ArXiv

  • Sewak, A., Inacio, V., Wuu, J., Benatar, M. and Hothorn, T. (2025+). Nonparanormal Modeling Framework for Prognostic Biomarker Assessment with Application to Amyotrophic Lateral Sclerosis. Submitted. ArXiv

  • Guevara, I. Inacio, V. and Gutierrez, L. (2024+). Bayesian model selection for analyzing predictor-dependent directional data. Submitted.

  • Margaritella, N., Inacio, V. and King, R. (2024+). A Bayesian functional PCA model with multilevel partition priors for group studies in neuroscience. Submitted. ArXiv

Articles published

  • Sharifi Far, S., Inacio, V., Evkaya, O. and Lenzi, A. (2025+). Hackathons in Statistics and Data Science Education and Experiences from ASA DataFest. Accepted at Teaching Statistics.

  • Rodriguez-Alvarez, M.X., Inacio, V and Klein, N. (2025). Density regression via Dirichlet process mixtures of normal structured additive regression models. Statistics and Computing, 35. [Link] Youtube

  • Wade, S. and Inacio, V. (2025). Dependent Bayesian mixture models: A predictive comparison. Statistical Science, 40, 81–108. [Link]

  • Inacio, V., de Carvalho, M., Jackson, O., McMahon, S. and Cockell, C. (2024). The need for large sample numbers to demonstrate that Martian environments are lifeless. Nature Astronomy, 8, 1493–1495. [Link]

  • Sharifi Far, S., Inacio, V., Paulin, D., de Carvalho, M., Augustin, N., Allerhand, M. and Robertson, G. (2023). Consultancy Style Dissertations in Statistics and Data Science: Why and How. The American Statistician, 77, 331–339. [Link]

  • Inacio, V. and Rodriguez-Alvarez, M.X. (2022). The Covariate-Adjusted ROC Curve: The Concept and Its Importance, Review of Inferential Methods, and a New Bayesian Estimator. Statistical Science, 37, 541–561. [Link]

  • Inacio, V. and Garrido Guillen, J.E. (2022). Bayesian nonparametric inference for the overlap coefficient: With an application to disease diagnosis. Statistics in Medicine, 41, 3879–3898. [Link]

  • Inacio, V., Lourenco, V., de Carvalho, M., Parker, R.A. and Gnanapragasam, V. (2021). Robust and flexible inference for the covariate-specific receiver operating characteristic curve. Statistics in Medicine, 40, 5779–5795. [Link].

  • Rodriguez-Alvarez, M.X. and Inacio, V. (2021). ROCnReg: An R Package for Receiver Operating Characteristic Curve Inference With and Without Covariates. The R Journal, 13, 525–555. [Link]

  • Margaritella, N., Inacio, V. and King, R. (2021). Parameter clustering in Bayesian functional principal component analysis of neuroscientific data. Statistics in Medicine, 40, 167–184. [Link]

  • Inacio, V., Rodriguez-Alvarez, M.X. and Gayoso-Diz, P. (2021). Statistical Evaluation of Medical Tests. Annual Review of Statistics and its Application, 8, 41–184. [Link]

  • Parker, R.A., Scott, C. , Inacio, V. and Stevens, N.T. (2020). Using multiple agreement methods for continuous repeated measures data: A tutorial for practitioners. BMC Medical Research Methodology, 20, 1–14. [Link]

  • Castro, L.M., Wang, W.L., Lachos, V.H., Inacio de Carvalho, V. and Bayes, C.L. (2019). Bayesian semiparametric modeling for HIV longitudinal data with censoring and skewness. Statistical Methods in Medical Research, 28, 1457–1476. [Link]

  • Hanson, T.E., Zhou, H. and Inacio de Carvalho, V. (2018). Bayesian nonparametric spatially smoothed density estimation. New Frontiers of Biostatistics and Bioinformatics (pp 87–105). Springer. [Link]

  • Inacio de Carvalho, V. and Rodriguez-Alvarez, M.X. (2018). Statistical Evaluation of Medical Diagnostic Tests. Wiley StatsRef: Statistics Reference Online (pp 1–13). [Link]

  • Inacio de Carvalho, V., de Carvalho, M. and Branscum, A.J. (2018). Bayesian bootstrap inference for the receiver operating characteristic surface. Stat, 7, e211. [Link]

  • Inacio de Carvalho, V. and Branscum, A.J. (2018). Bayesian nonparametric inference for the three-class Youden index and its associated optimal cutoff points. Statistical Methods in Medical Research, 27, 689–700. [Link]

  • Inacio de Carvalho, V., de Carvalho, M. and Branscum, A.J. (2017). Nonparametric Bayesian covariate-adjusted estimation of the Youden index. Biometrics, 73, 1279–1288. [Link]

  • Inacio de Carvalho, V., de Carvalho, M., Alonzo, T.A. and Gonzalez-Manteiga, W. (2016). Functional covariate-adjusted partial area under the specificity-ROC curve with an application to metabolic syndrome diagnosis. Annals of Applied Statistics, 10, 1472–1495. [Link]

  • Inacio de Carvalho, V., de Carvalho, M. and Jara, A. (2015). Bayesian nonparametric approaches for ROC curve inference. Nonparametric Bayesian Inference in Biostatistics (pp 327–344). [Link]

  • Inacio de Carvalho, V., Jara, A., Hanson, T.E., and de Carvalho, M. (2013). Bayesian nonparametric ROC regression modeling. Bayesian Analysis, 8, 623–646. [Link]

  • Inacio, V., Gonzalez-Manteiga, W., Febrero-Bande, M., Gude, F., Alonzo, T.A. and Cadarso-Suarez, C. (2012). Extending induced ROC methodology to the functional context. Biostatistics, 13, 594–608. [Link]

  • Inacio, V., Turkman, M.A., Nakas, C.T. and Alonzo, T. A. (2011). Nonparametric Bayesian estimation of the three-way receiver operating characteristic surface. Biometrical Journal, 53, 1011–1024. [Link]

Contributions to Papers with Discussion

  • Inacio, V., de Carvalho, M. and Turkman, M. A. (2012). A discussion on “Probabilistic Index Models” by Thas, O., de Neve, J., Lieven, C. and Ottoy, J.P. in Journal of the Royal Statistical Society, Ser. B, 74, 623–671. [Link]

Edited Special Issue

  • Inacio de Carvalho, V., de Carvalho, M. and Gonzalez-Manteiga, W. (2014). “Statistical Models for Diagnosis and ROC Analysis”. RevStat–Statistical Journal, 12 [Link]

PhD thesis

  • Semiparametric and nonparametric modeling of diagnostic data (2012). [Link]