Personale

Recapiti

Orario di ricevimento

Italiano

Biografia

Curriculum

Interessi

Note

Pubblicazioni

Insegnamenti

Tematiche di tesi

English

Biography

Curriculum

Interest

Maria Francesca MARINO

Ruolo attuale:: Professore Associato
SSD:: STAT-01/A - Statistica
Afferenza organizzativa:: Dipartimento di Statistica, Informatica, Applicazioni 'G. Parenti' (DiSIA)

Recapiti

	0552751569
	mariafrancesca.marino(AT)unifi.it

Avvisi

Statistical Analysis of Network Data — Classes Begin September 21

The Statistical Analysis of Network Data course will officially start on September 21.

Statistica - partizione JZ / Statistica per le Scienze Sociali — Inizio lezioni il 15 settembre

Il corso di Statistica - partizione JZ / Statistica per le Scienze Sociali avrà ufficialmente inizio il 15 settembre alle ore 14.30 -- Aula D4/005.

Maria Francesca MARINO

Orario di ricevimento (aggiornato al 08/09/2026)

Mercoledi 9.20-11.30 (inviare mail per fissare l'appuntamento) - Wednesay 9.30 - 11.30 (send an email to make an appointment)

Maria Francesca MARINO

Biografia

Maria Francesca Marino è Professoressa Associata di Statistica (STAT-01/A) presso il Dipartimento di Statistica, Informatica Applicazioni "G. Parenti" dell'Università di Firenze, dove insegna diversi corsi di Statistica di base ed avanzati nei programmi di Laurea Triennale e Magistrale. La sua ricerca si concentra principalmente sullo sviluppo e la stima di modelli a variabili latenti per dati caratterizzati da forme di dipendenza complessa. Tra questi rientrano dati longitudinali, dati multi-livello e reti.

Maria Francesca MARINO

Curriculum

Posizioni ricoperte

Professore Associato in Statistica (STAT-01/A), Università degli Studi di Firenze - Dipartimento di Statistica, Informatica e Applicazioni (dal 2023);
Ricercatore a tempo determinato (RTDb) in Statistica (SECS/S-01),Università degli Studi di Firenze - Dipartimento di Statistica, Informatica e Applicazioni (dal 2020-2023);
Ricercatore a tempo determinato (RTDa) in Statistica Sociale (SECS/S-05), Università degli Studi di Firenze - Dipartimento di Statistica, Informatica e Applicazioni (dal 2017-2020);
Assegnista di ricerca in Statistica (SECS/S-01), Università degli Studi di Perugia - Dipartimento di Scienze politiche (2016 - 2017);
Assegnista di ricerca in Statistica (SECS/S-01), Università degli Studi di Perugia - Dipartimento di Economia (2015 - 2016);

Formazione

Dottorato di ricerca in Statistica Metodologica, Sapienza, Università di Roma - Dipartimento di Scienze Statistiche. Titolo tesi: Handling time-constant and time-varying unobserved heterogeneity in longitudinal data models (2011 - 2014);
Laurea magistrale in Scienze Statistiche e Decisionali, Sapienza, Università di Roma - Dipartimento di Scienze Statistiche. (2008 - 2011);
Laurea triennale in Statistica e Informatica per la Gestione delle Imprese,Università degli Studi di Perugia (2005 - 2008);

Interessi di ricerca

Modelli a variabili latenti per dati longitudinali e multi-livello;
Modelli per l'analisi delle reti;
Modelli lineari generalizzati, regressione quantile ed M-quantile
Small area estimation;
Model-based clustering e biclustering;
Trattamento dei dati mancati.

Esperienza internazionale

Visiting Research Student, Centre for Research into Ecological and Environmental Modelling. School of Mathematics and Statistics. St Andrews, Scottland (2013);
Visiting Research Student, Department of Social Statistics and Demography. Faculty of Social Science. Southampton, UK (2014).

Attività istituzionale e scientifica

Delegato Erasmus per il corso di laurea magistrale in Statistica e Data Science, Scuola di Economia e Management - Università degli Studi di Firenze (dal 2017 al 2024);
Membro del comitato per la didattica per il corso di laurea magistrale in Statistica e Data Science, Scuola di Economia e Management - Università degli Studi di Firenze (dal 2017 al 2024);
Membro del comitato per la didattica per il corso di laurea magistrale in Geoengeenering, Scuola di Ingegneria - Università degli Studi di Firenze (dal 2017 al 2020);
Membro del comitato ordinatore per il Master in Data Science and Statistical Learning, Scuola di Economia e Management - Università degli Studi di Firenze (dal 2023);
Docente del Laboratorio "Didattica della Statistica" nell'ambito del progetto "PF60", volto a rafforzare le competenze degli insegnanti della scuola secondaria (dal 2024);
Docente per il corso di Master in Data Science and Statistical Learning, Scuola di Economia e Management - Università degli Studi di Firenze (dal 2021);
Docente per il corso di Master in Digital Transofrmation, Scuola di Scienze Politiche - Università degli Studi di Firenze (dal 2020);
Membro della Società Italiana di Statistica (dal 2012).

Attività editoriale

Associate Editor per Journal of the Royal Statistical Society - Serie C (since 2025)

Revisore per le seguenti riviste:

Biometrical Journal;
Metron;
Computational Statistics and Data Analysis;
Statistics in Medicine;
Social Networks;
Statistics in Transition;
Statistical Methods and Applications;
Journal of the American Statistical Society;
International Statistical Review;
Journal of Applied Statistics Journal of the Royal Statistical Society - Serie A;
Journal of Statistical Computation and Simulation;
Biostatistics;
Statistics and Computing;
Journal of Classificaiton;
Statistical Methods & Applications.

Maria Francesca MARINO

Interessi

1. Regressione: modelli lineari, modelli lineari generalizzati, regressione quantile ed M-quantile
2. Modelli a variabili latenti: modelli a mistura finita e modelli hidden Markov
3. Analisi di dati longitudinali e multilivello
4. Missing data
5. Network Data Analysis
6. Stima per piccole aree

Maria Francesca MARINO

Note

Maria Francesca MARINO

Pubblicazioni

Legenda

Contributo su rivista |

Articolo su libro |

Libro |

Contributo in atti di convegno (proceeding) |

Brevetto |

Curatela | Altro

Altro |

Tesi di Dottorato

Alfo' MARCO, marino MARIA FRANCESCA, Martella FRANCESCA (In corso di stampa). Biclustering multivariate discrete longitudinal data. STATISTICS AND COMPUTING, vol. 34, pp. 0-0, ISSN:1573-1375 DOI

dalila failli; maria francesca marino; francesca martella (2026). Mixture-Based Latent Trait Modeling for Biclustering Overdispersed Counts. In: Paula Brito, Francesco Denti, Francesca Greselin, Krzysztof Jajuga, Mariangela Zenga. Navigating Complexity: Statistical Methods, Data Analysis, and Machine Learning for Actionable Insights, pp. 170-177 Springer.

Dalila Failli; Maria Francesca Marino; Francesca Martella (2026). Approximate Inference for Mixtures of Latent Trait Analyzers. In: Paula Brito, Francesco Denti, Francesca Greselin, Krzysztof Jajuga, Mariangela Zenga. Navigating Complexity: Statistical Methods, Data Analysis, and Machine Learning for Actionable Insights, pp. 162-169 Springer.

Failli, Dalila; Marino, Maria Francesca; Arpino, Bruno (2025). Hierarchical Mixtures of Latent Trait Analyzers with concomitant variables for multivariate binary data. STATISTICS AND COMPUTING, vol. 35, pp. 0-0, ISSN:0960-3174 DOI

dalila failli, maria francesca marino, francesca martella (2025). Mixtures of Generalized Latent Trait Analyzers for Biclustering Multivariate Data. In: SIS 2024 International Meeting, Springer, Cham, pp. 635-639, ISBN:978-3-031-64430-6

Failli, Dalila; Marino, Maria Francesca; Martella, Francesca (2025). Mixture of Experts Latent Trait Analyzers. In: Antonio D'Ambrosio, Markde Rooij, Kim De Roover, Carmela Iorio, Michele La Rocca. Supervised and Unsupervised Statistical Data Analysis, pp. 272-281 D'Ambrosio, A., de Rooij, M., De Roover, K., Iorio, C., La Rocca, M, ISBN:9783032030412. DOI

Failli, Dalila; Marino, Maria Francesca; Martella, Francesca (2025). A Novel Approach for Biclustering Bipartite Networks: An Extension of Finite Mixtures of Latent Trait Analyzers. JOURNAL OF CLASSIFICATION, pp. 0-0, ISSN:0176-4268 DOI

Marco Alfò, Maria Francesca Marino, Maria Giovanna Ranalli, Nicola Salvati (2025). lqmix: an R Package for Longitudinal Data Analysis via Linear Quantile Mixtures. THE R JOURNAL, pp. 188-211, ISSN:2073-4859

Failli Dalila, MARIA FRANCESCA MARINO, Francesca Martella (2025). Dynamic Mixture of Latent Trait Analyzers for Clustering Longitudinal. In: SIS 2025, Genova, Enrico Di Bella, Vincenzo Gioia, Corrado Lagazio, Susanna Zaccaria, pp. 0-0, ISBN:9783031967351

Marco Alfo', Maria Francesca Marino, Francesca Martella (2024). Finite mixtures of linear quantile regressions with concomitant variables: a simple solution to endogeneity in longitudinal data models. In: The 52nd Scientific Meeting of the Italian Statistical Society, Alessio Pollice, Paolo Mariani, pp. 0-0, ISBN:978-3-031-64352-1

Marino, Maria Francesca (2024). Book review. THE AMERICAN STATISTICIAN, vol. 78, pp. 128-129, ISSN:0003-1305 DOI Accesso ONLINE all'editore

Dalila Failli; Maria Francesca Marino; Francesca Martella (2024). Biclustering of discrete data by extended finite mixtures of latent trait models. In: Statistics and Data Science Conference, Antonella Plaia; Leonardo Egidi; Antonino Abbruzzo, pp. 264-269, ISBN:978-88-5509-645-4

Failli, Dalila; Maria Francesca Marino; Martella, Francesca (2024). Finite mixtures of latent trait analyzers with concomitant variables for bipartite networks: an analysis of COVID-19 data. MULTIVARIATE BEHAVIORAL RESEARCH, vol. 59, pp. 801-817, ISSN:1532-7906 DOI

Dalila Failli, Bruno Arpino, Maria Francesca Marino, Emilio Zagheni (2024). Analysis of the digital divide through Facebook data: a Finite Mixture approach. In: ICES 2024 - 2nd Italian Conference on Economic Statistics, Elena Fabrizi, Francesca Adele Giambona, Caterina Marini, Andrea Marletta, Antonella Rocca, pp. 97-100, ISBN:978-88-476-2950-9

marino maria francesca (2024). Applied Linear Regression for Longitudinal Data: With an Emphasis on Missing Observations. THE AMERICAN STATISTICIAN, vol. 78, pp. 128-129, ISSN:1537-2731

dalila failli, bruno arpino, maria francesca marino (2024). A finite mixture approach for the analysis of digital skills in Bulgaria, Finland and Italy: the role of socio-economic factors. STATISTICAL METHODS & APPLICATIONS, vol. 33, pp. 1483-1511, ISSN:1618-2510 DOI

Alfo Marco; Marino Maria Francesca; Martella Francesca (2024). Biclustering multivariate discrete longitudinal data. STATISTICS AND COMPUTING, vol. 34, pp. 1-21, ISSN:1573-1375 DOI

Dalila Failli; Maria Francesca Marino; Bruno Arpino (2024). Hierarchical Mixtures of Latent Trait Analyzers with concomitant variables. In: Statistics and Data Science Conference, Antonella Plaia; Leonardo Egidi ; Antonino Abbruzzo, pp. 84-89, ISBN:978-88-5509-645-4

Dalila Failli, Bruno Arpino, Maria Francesca Marino, Francesca Martella (2024). A Biclustering Approach via Mixture of Latent Trait Analyzers for the Analysis of Digital Divide in Italy. In: Jochen Einbeck, Hyeyoung Maeng, Emmanuel Ogundimu, Konstantinos Perrakis. Developments in Statistical Modelling, pp. 102-108 Springer, ISBN:978-3-031-65722-1. DOI

Marco Alfò, Maria Francesca Marino, Silvia D’Elia (2023). Modelling ordinal response to treatment in a real-world cohort study. In: SIS 2023: Statistical Learning, Sustainability and Impact Evaluation, Francesco Maria Chelli, Mariateresa Ciommi, Salvatore Ingrassia, Francesca Mariani, Maria Cristina Recchioni, pp. 0-0, ISBN:9788891935618

Dalila Failli, Maria Francesca Marino, Francesca Martella (2023). An extension of finite mixtures of latent trait analyzers for biclustering bipartite networks. In: SIS 2023: Statistical Learning, Sustainability and Impact Evaluation, Francesco Maria Chelli, Mariateresa Ciommi, Salvatore Ingrassia, Francesca Mariani, Maria Cristina Recchioni, pp. 0-0, ISBN:9788891935618

Maria Francesca Marino, Matteo Sani, Monia Lupparelli (2023). Multi-level stochastic block models for multiplex networks. In: 14th Scientific Meeting of the Classification and Data Analysis Group Salerno, Pietro Coretto, Giuseppe Giordano, Michele La Rocca, Maria Lucia Parrella, Carla Rampichini, pp. 0-0, ISBN:978-88-9193-563-2

Leonardo, Grilli; Maria, Francesca Marino; Omar, Paccagnella; Carla, Rampichini (2022). Multiple imputation and selection of ordinal level 2 predictors in multilevel models: An analysis of the relationship between student ratings and teacher practices and attitudes. STATISTICAL MODELLING, vol. 22, pp. 221-238, ISSN:1471-082X DOI Accesso ONLINE all'editore

Marino Maria Francesca, Silvia Pandolfi (2022). Hybrid maximum likelihood inference for stochastic block models. COMPUTATIONAL STATISTICS & DATA ANALYSIS, vol. 171, pp. 0-0, ISSN:0167-9473 DOI

Montanari G.E.; Doretti M.; Marino M.F. (2022). Model-based two-way clustering of second-level units in ordinal multilevel latent Markov models. ADVANCES IN DATA ANALYSIS AND CLASSIFICATION, vol. 16, pp. 457-485, ISSN:1862-5347 DOI

Dalila Failli, Marino Maria Francesca, Francesca Martella (2022). Extending finite mixtures of latent trait analyzers for bipartite networks. In: 51th Scientific Meeting of the Italian Statistical Society, Caserta, Antonio Balzanella, Matilde Bini, Carlo Cavicchia, Rosanna Verde, pp. 540-550, ISBN:9788891932310

Alfò M.; Marino M.F.; Ranalli M.G.; Salvati N.; Tzavidis N. (2021). M-quantile regression for multivariate longitudinal data with an application to the Millennium Cohort Study. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, vol. 70, pp. 122-146, ISSN:0035-9254 DOI

Emilia Rocco; Maria Francesca Marino (2021). Small area estimation via multivariate generalized linear mixed effects models. In: SAE2021: Conference on Big Data for Small Area Estimation - BIG4small (SAE2021 - www.sae2021.org) - a Satellite Meeting of the International Statistical Institute 63rd World Statistics, Università degli Studi di Napoli Federico II - Convegno on-line, September 20-24, 2021, Edizioni Zaccaria, pp. 106-111, ISBN:9788899594138 Accesso ONLINE all'editore

M.G. Ranalli, M.F. Marino, N. Salvati , M. Alfò (2021). Empirical Best Prediction for Small Area Estimation of categorical variables using Finite Mixtures of Multinomial Logistic Models. In: SAE2021: Conference on Big Data for Small Area Estimation - BIG4small (SAE2021 - www.sae2021.org) - a Satellite Meeting of the International Statistical Institute 63rd World Statistics, Napoli, Edizioni Zaccaria, pp. 92-97, ISBN:9788899594138

Marino, Maria Francesca; Alfò, Marco (2020). Finite Mixtures of Hidden Markov Models for Longitudinal Responses Subject to Drop out. MULTIVARIATE BEHAVIORAL RESEARCH, vol. 55, pp. 647-663, ISSN:0027-3171 DOI

Cristiana Sacco, Rosa Donato, Beatrice Zanella, Gabriella Pini, Lilia Pettini, Maria Francesca Marino, Anubha Devi Rookmin, Massimiliano Marvasi (2020). Mycotoxins and flours: Effect of type of crop, organic production, packaging type on the recovery of fungal genus and mycotoxins. INTERNATIONAL JOURNAL OF FOOD MICROBIOLOGY, pp. 0-0, ISSN:0168-1605

Del Sarto, Simone; Marino, Maria Francesca; Ranalli, Maria Giovanna; Salvati, Nicola (2019). Using finite mixtures of M-quantile regression models to handle unobserved heterogeneity in assessing the effect of meteorology and traffic on air quality. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, vol. ..., pp. 0-0, ISSN:1436-3240 DOI

Elena Pirani, Maria Francesca Marino, Alessandra Petrucci (2019). Correlates of inter-districts migrations in Tanzania. a gravity-type modeling approach. STATISTICA, vol. 79, pp. 201-221, ISSN:1973-2201 DOI

Maria Francesca Marino; Maria Giovanna Ranalli; Nicola Salvati; Marco Alfo' (2019). Semiparametric empirical best prediction for small area estimation of unemployment indicators. THE ANNALS OF APPLIED STATISTICS, vol. 13, pp. 1187-1218, ISSN:1932-6157 DOI

Bruckschen, Fabian; Koebe, Till; Ludolph, Melina; Marino, Maria Francesca; Schmid, Timo (2019). Refugees in Undeclared Employment—A Case Study in Turkey. In: Fabian Bruckschen, Till Koebe, Melina Ludolph, Maria Francesca Marino, Timo Schmid. Guide to Mobile Data Analytics in Refugee Scenarios, pp. 329-346 Albert Ali Salah, Alex Pentland, Bruno Lepri, Emmanuel Letouzé, ISBN:978-3-030-12553-0. DOI

Marino Maria Francesca; Silvia Pandolfi (2019). Dynamic clustering of network data: a hybrid maximum likelihood approach. In: 12th Scientific Meeting of the CLAssification and Data Analysis Group, Cassino, G.C. Porzio, F. Greselin, S. Balzano, pp. 313-316, ISBN:978-88-8317-108-6

Simone Del Sarto, Maria Francesca Marino, Maria Giovanna Ranalli,Nicola Salvati (2018). Modelling the effect of traffic and meteorology on air pollution with finite mixtures of M-quantile regression models. In: 49th Scientific meeting of the Italian Statistical Society, Antonino Abbruzzo, Eugenio Brentari, Marcello Chiodi e Davide Piacentino, pp. 0-0, ISBN:9788891910233

Marino, Maria Francesca; Tzavidis, Nikos; Alfò, Marco (2018). Mixed hidden Markov quantile regression models for longitudinal data with possibly incomplete sequences. STATISTICAL METHODS IN MEDICAL RESEARCH, vol. 27, pp. 2231-2246, ISSN:0962-2802 DOI Accesso ONLINE all'editore

Bartolucci, Francesco; Marino, Maria Francesca; Pandolfi, Silvia (2018). Dealing with reciprocity in dynamic stochastic block models. COMPUTATIONAL STATISTICS & DATA ANALYSIS, vol. 123, pp. 86-100, ISSN:0167-9473 DOI

Maria Francesca Marino; Alessandra Petrucci; Elena Pirani (2018). Environmental shocks and internal migration in Tanzania. In: 49th Scientific meeting of the Italian Statistical Society, Antonino Abbruzzo, Eugenio Brentari, Marcello Chiodi e Davide Piacentino, pp. 0-0, ISBN:9788891910233

Maria Francesca Marino; Carla Rampichini (2018). Multilevel analysis of student ratings with missing level-two covariates: a comparison of imputation techniques. In: 49th Scientific meeting of the Italian Statistical Society, Antonino Abbruzzo, Eugenio Brentari, Marcello Chiodi e Davide Piacentino, pp. 0-0, ISBN:9788891910233

Leonardo Grilli, Maria Francesca Marino, Omar Paccagnella, Carla Rampichini (2018). Multiple imputation and selection of ordinal level-2 predictors in multilevel models. In: ASMOD 2018 : Advanced Statistical Modelling for Ordinal Data, Napoli, 24-26 October 2018, FedOAPress - Federico II Open Access University Press, pp. 133-138, ISBN:978-88-6887-042-3 DOI

Francesco Bartolucci; Maria Francesca Marino; Silvia Pandolfi (2018). Dealing with reciprocity in dynamic stochastic block models. In: 49th Scientific meeting of the Italian Statistical Society, Antonino Abbruzzo, Eugenio Brentari, Marcello Chiodi e Davide Piacentino, pp. 0-0, ISBN:9788891910233

Alessandra Spagnoli; Maria Francesca Marino; and Marco Alfo' (2018). A bi-dimensional finite mixture model for longitudinal data subject to dropout. STATISTICS IN MEDICINE, vol. 37, pp. 2998-3011, ISSN:1097-0258 DOI

Marco Alfò; Maria Francesca Marino (2018). Dependence and sensitivity in regression models for longitudinal responses subject to dropout. In: 49th Scientific meeting of the Italian Statistical Society, Antonino Abbruzzo, Eugenio Brentari, Marcello Chiodi e Davide Piacentino, pp. 0-0, ISBN:9788891910233

Marino, Maria Francesca; Alfò, Marco (2017). Dynamic random coefficient based drop-out models for longitudinal responses. In: Conference of the Italian Statistical Society 2017 - Statistics and Data Science: new challenges, new generations, Università degli Studi di Firenze, pp. 0-0, ISBN:9788864535210

Marino, Maria Francesca; Alfó, Marco (2016). Gaussian quadrature approximations in mixed hidden Markov models for longitudinal data: A simulation study. COMPUTATIONAL STATISTICS & DATA ANALYSIS, vol. 94, pp. 193-209, ISSN:0167-9473 DOI Accesso ONLINE all'editore

Alfò, Marco; Marino, Maria Francesca; Ranalli, Maria Giovanna; Salvati, Nicola (2016). M-quantile regression for multivariate longitudinal data. In: 48th scientific meeting of the Italian Statistical Society, Pratesi Monica.; Perna Cira, pp. 0-0, ISBN:9788861970618

Marino, Maria Francesca; Alfó, Marco (2015). Latent drop-out based transitions in linear quantile hidden Markov models for longitudinal responses with attrition. ADVANCES IN DATA ANALYSIS AND CLASSIFICATION, vol. 9, pp. 483-502, ISSN:1862-5347 DOI Accesso ONLINE all'editore

Marino, Maria Francesca; Farcomeni, Alessio (2015). Linear quantile regression models for longitudinal experiments: an overview. METRON, vol. 73, pp. 229-247, ISSN:0026-1424 DOI Accesso ONLINE all'editore

Marino, Maria Francesca; Tzavidis, Nikos (2014). Mixed hidden Markov models for quantiles. In: 47th Scientific Meeting of the Italian Statistical Society, Cabras S.; Di Battista T.; Racugno W., pp. 0-0, ISBN:9788884678744

Marino, Maria Francesca; Alfò, Marco (2013). Latent drop-out hidden Markov model with mixed effects. In: Conference of the Italian Statistical Society 2013, Advances in Latent Variables - Methods, Models and Application, Carpita, Maurizio; Brentari, Eugenio; Qannari, El, pp. 0-0, ISBN:978 88 343 2556 8

Maria Francesca MARINO

ppp

Tematiche di tesi

Network data analysis

Latent variable modeling for complex data structures

Quantile regression

Model-based clustering and biclustering

Maria Francesca MARINO

Biography

Maria Francesca Marino is an Associate Professor of Statistics (STAT-01/A) at the Department of Statistics, Computer Science, and Applications "G. Parenti" of the University of Florence, where she teaches several basic and advanced Statistics courses in Bachelor's and Master's degree programs. Her research primarily focuses on the development and estimation of latent variable models for data characterized by complex dependence structures, including longitudinal data, multilevel data, and networks.

Maria Francesca MARINO

Curriculum

Positions Held

Associate Professor of Statistics (STAT-01/A), University of Florence – Department of Statistics, Computer Science, and Applications (since 2023);
Assistant Professor (RTDb) in Statistics (SECS/S-01), University of Florence – Department of Statistics, Computer Science, and Applications (2020–2023);
Assistant Professor (RTDa) in Social Statistics (SECS/S-05), University of Florence – Department of Statistics, Computer Science, and Applications (2017–2020);
Research Fellow in Statistics (SECS/S-01), University of Perugia – Department of Political Science (2016–2017);
Research Fellow in Statistics (SECS/S-01), University of Perugia – Department of Economics (2015–2016).

Education

PhD in Methodological Statistics, Sapienza University of Rome – Department of Statistical Sciences. Dissertation title: Handling time-constant and time-varying unobserved heterogeneity in longitudinal data models (2011–2014);
Master's Degree in Statistical and Decision Sciences, Sapienza University of Rome – Department of Statistical Sciences (2008–2011);
Bachelor's Degree in Statistics and Computer Science for Business Management, University of Perugia (2005–2008).

Research Interests

Latent variable models for longitudinal and multilevel data;
Models for network analysis;
Generalized linear models, quantile and M-quantile regression;
Small area estimation;
Model-based clustering and biclustering;
Missing data.

International Experience

Visiting Research Student, Centre for Research into Ecological and Environmental Modelling, School of Mathematics and Statistics, St Andrews, Scotland (2013);
Visiting Research Student, Department of Social Statistics and Demography, Faculty of Social Science, University of Southampton, UK (2014).

Institutional and Scientific Activities

Erasmus Coordinator for the Master's Degree in Statistics and Data Science, School of Economics and Management – University of Florence (2017–2024);
Member of the Teaching Committee for the Master's Degree in Statistics and Data Science, School of Economics and Management – University of Florence (2017–2024);
Member of the Teaching Committee for the Master's Degree in Geoengineering, School of Engineering – University of Florence (2017–2020);
Lecturer for the "Didattica della Statistica" Laboratory within the PF60 project, aimed at enhancing statistical teaching skills for secondary school teachers (since 2024);
Lecturer for the Master's Degree in Data Science and Statistical Learning, School of Economics and Management – University of Florence (since 2021);
Lecturer for the Master's Degree in Digital Transformation, School of Political Science – University of Florence (since 2020);
Member of the Italian Statistical Society (since 2012).

Editorial Activities

Associate Editor for Journal of the Royal Statistical Society – Series C (since 2025).

Reviewer for the following journals:

Biometrical Journal
Metron
Computational Statistics and Data Analysis
Statistics in Medicine
Social Networks
Statistics in Transition
Statistical Methods and Applications
Journal of the American Statistical Association
International Statistical Review
Journal of Applied Statistics
Journal of the Royal Statistical Society – Series A
Journal of Statistical Computation and Simulation
Biostatistics
Statistics and Computing
Journal of Classification
Statistical Methods & Applications

Maria Francesca MARINO

Interest

1. Regression: linear models, generalized linear models, quantile and M-quantile regression
2. Latent variable models: mixtures and hidden Markov models
3. Longitudinal and multi-level data analysis
4. Missing data analysis
5. Network Data Analysis
6. Model-based clustering and biclustering

Area riservata