Papers published in referred journals

Aliverti, E. and Russo, M. Dynamic modeling of the Italians’ attitude towards Covid-19, Statistics in Medicine, in press, DOI:10.1002/sim.9560

Lauffenburger, J. C., K. Choudhry, N. K., Russo, M., Glynn, R. J., Ventz, S., Trippa, L. Leveraging adaptive trials to evaluate interventions in health services research. BMJ Medicine 2022;1:e000158. doi: 10.1136/bmjmed-2022-000158

Russo, M., Ventz, S., Wang, V., Trippa, L. (2021). Inference in response-adaptive clinical trials when the enrolled population varies over time. Biometrics, 00 1 - 13. https://doi.org/10.1111/biom.13582

Aliverti, E. and Russo, M. (2021). Stratified stochastic variational inference for high-dimensional network factor model Journal of Computational and Graphical Statistics, 31:2, 502-511, DOI: 10.1080/10618600.2021.1984929

Russo, M., Singer, B. H. & Dunson, D. B. (2021). Multivariate mixed membership modeling: Inferring domain-specific risk profiles. The Annals of Applied Statistics, 16(1): 391 - 370, DOI: 10.1214/21-AOAS1496

Rigon, T., Aliverti, E., Russo, M. , and Scarpa, B, (2021) A discussion on: Centered partition processes: Informative priors for clustering by Paganin, S., Herring, A. H., Olshan, A. F. and Dunson, D. B. Bayesian Analysis 16(1): 301-370.

Ottaviano, G., Nardello, E., Pendolino, A. L., Pozza, M. D., Russo, M. , Savietto, E. Peter, J. A., Ermolao, A., (2020). Nasal Function Changes at High Altitude, American Journal of Rhinology & Allergy, 34(5) 618-625.

Aliverti, E., Paganin, S., Rigon, T. and Russo, M. (2019). A discussion on: “ Latent nested nonparametric priors” by Camerlenghi, F., Dunson, D.B., Lijoi, A., Prünster, I. and Rodriguez, A. in Bayesian Analysis 14(4): 1303–1356.

Ottaviano, G., Pendolino, A. L., Nardello, E., Maculan, P., Martini, A., Russo, M. , and Lund, V. J (2019). Peak nasal inspiratory flow measurement and visual analogue scale in a large adult population, Clinical Otolaryngology; 44: 541–548.

Russo, M., Durante, D. and Scarpa B. (2018). Bayesian Inference on Group Differences in Multivariate Categorical Data, Computational Statistics & Data Analysis, 126, 136–149

Cantone, E., Ciofalo, A.,Vodicka, J., Iacono, V., Mylonakis, I., Scarpa, B.,Russo, M., Iengo, M., de Vincentiis, M., Martini, A. and Ottaviano, G. , Pleasantness of olfactory and trigeminal stimulants in different Italian regions., European Archives of Oto-Rhino-Laryngology, 1–-7, 2017

Peer reviewed proceedings & book chapters

Russo, M. and Scarpa B. (2021). Learning in medicine: the importance of statistical thinking. Springer Nature, Method in Molecular Biology, in press.

Russo, M. (2021). Malaria risk detection via mixed membership models. CLADAG 2021 book of abstract and short papers.

Cabassi, A., Casa, A., Fontana, M., Russo, M. and Farcomeni, A. (2018). Three testing perspectives on connectome data. Springer Proceedings in Mathematics & Statistics, vol 257, 37–55. Springer, Cham.

Russo, M. (2017). Detecting Group Differences in Multivariate Categorical Data. Proceedings the Italian Statistical Society, Firenze University Press, ISBN 9788891927361.

Under review

Russo, M., Paganin S., and Scarpa~B. Modeling students’ ability: a generalized partial credit model for network dependent latent traits.