Prof. Elena Stanghellini

 

Click here for my contact details and web page.

At 360 Port Avenue, with Elizabeth, John and Marco

Research interests

All my research has been devoted to Graphical Markov Models. The class of Graphical Markov Models is so vast that includes many existing models, like Structural Equation Models, log-linear models, and so on, that I never get tired in exploring them from the theoretical point of view and in using them in applied data analysis.

 

From the theoretical point of view, I have been attracted by issues on distortion induced by unobserved factors or by informative selection. For that, I have developed conditions for identification of the parameters of interest as well as tools to perform sensitivity analysis or to construct uncertainty intervals. All these issues are strongly linked to causal inference and mediation analysis.

Applied research interests include both biomedical issues (some of them linked to COVID-19, see paper 2 and 7, below) and micro-economic and financial data (see e.g. paper 3 and 4, below).

 

Papers on peer reviewed scientific journals (since 2004)

  1. STANGHELLINI E., DORETTI M., TEZUKA T. (2024). A note on “Simple graphical rules to assess selection bias in general-population and selected-sample treatment effects” by M. B. Mathur and I. Shpitser. American Journal of Epidemiology. Forthcoming. https://doi.org/10.1093/aje/kwae337
  2. GOURGOURA K., RIVADENEIRA P., STANGHELLINI E., CARONI C., BARTOLUCCI F., …, PUCCI G., VAUDO G. (2024). Modelling the long term impact of COVID-19 using Graphical Chain Model. BMC Infectious Diseases. https://bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-024-09777-0
  3. DE NOVELLIS G., MUSILE TANZI P., STANGHELLINI E. (2024). Covenant-lite agreement and credit risk: a key relationsjip on the leveraged loan market. Research In International Business and Finance, ISSN 0275-5319, E-ISSN 1878-3384, Vol. 70, no Part B, article id 102377. 10.1016/j.ribaf.2024.102377
  4. DA FERMO C., MUSILE TANZI P., NICOLOSI M., STANGHELLINI E. (2024). "On the relationship between Financial and Sustainable variables: Insights from Graphical Gaussian Model”. Journal of Financial Management, Markets and Institutions.  http://dx.doi.org/10.2139/ssrn.4312617
  5. DORETTI M., GENBÄCK, M., STANGHELLINI E. (2024). “Mediation analysis with case-control sampling: Identification and estimation in the presence of a binary mediator”. Biometrical Journal. https://doi.org/10.1002/bimj.202300089.
  6. DE NOVELLIS G., MUSILE TANZI P., RANALLI G., STANGHELLINI E. (2024). “Leveraged finance exposure in the banking system: Systemic risk and interconnectedness”. Journal of International Financial Markets, Institutions and Money, Vol. 90. https://doi.org/10.1016/j.intfin.2023.101890.
  7. LANZILAO L., MARINIELLO A., POLENZANI B., ALDINUCCI A., NAZERIAN P., PROTA A., GRIFONI S., TONIETTI B., NERI C., TURCO L., FANELLI A., AMEDEI A., STANGHELLINI E. (2023). “A Computational Approach in the Diagnostic Process of COVID-19: The Missing Link between the Laboratory and Emergency Department”. Frontiers in Bioscience (Landmark Ed). https://pubmed.ncbi.nlm.nih.gov/36866553/
  8. GUERRANTI R., FASANO T., …, LANZILAO L., STANGHELLINI E., GIAVARINA D., RIVA G., PADOAN A. (2022) “Big data e intelligenza artificiale in medicina di laboratorio - Artificial intelligence and big data in laboratory medicine” Biochimica Clinica; 47(1) 074-08. (On Line) doi: 10.19186/BC_2022.080
  9. STANGHELLINI E., KATERI M. (2022). “Exact Parametric Mediation for Ordinal Outcome and Binary Mediator”. Epidemiology, Vol. 33(6), pp. 840-842 https://pubmed.ncbi.nlm.nih.gov/36220580/
  10. DORETTI M., RAGGI M., STANGHELLINI E. (2022) “Exact parametric causal mediation with a binary outcome with a binary mediator”. Statistical Methods and its Application, Vol. 31, pp. 87–108, https://link.springer.com/article/10.1007/s10260-021-00562-w. Published online first in 2021.
  11. RAGGI M., STANGHELLINI E., DORETTI M. (2021). “Path Analysis for Binary Random Variables”. Sociological Methods and Research. Published online first. https://doi.org/10.1177/00491241211031260
  12. DORETTI M., RAGGI M., STANGHELLINI E. (2021) “Exact parametric causal mediation with a binary outcome with a binary mediator”. Statistical Methods and its Application. Published online first. https://link.springer.com/article/10.1007/s10260-021-00562-w
  13. STANGHELLINI E., DORETTI M. (2019). “On marginal and conditional parameters in logistic regression models”. Biometrika, Vol. 106, 3, pp. 732–739.
  14. DORETTI M., GENELETTI S., STANGHELLINI E. (2018). “Missing Data: A Unified Taxonomy Guided by Conditional Independence”. International Statistical Review, Vol. 86, 2, pp. 189-204.
  15. GENBÄCK, M., NG. N., STANGHELLINI E., DE LUNA X. (2017). “Predictors of decline in self-reported health: addressing non-ignorable dropout in longitudinal studies of aging”. European Journal of Ageing.  https://doi.org/10.1007/s10433-017-0448-x
  16. MEALLI F., PACINI B., STANGHELLINI E. (2016). “Identification of principal causal effects using secondary outcomes in concentration graphs”. Journal of Educational and Behvioural Statistics, doi:10.3102/1076998616646199. Vol. 41, pp. 463-480.
  17. DORETTI M., GENELETTI S., STANGHELLINI E. (2016). “Tackling non.ignorable dropout in the presence of time varying confounding”. Journal of the Royal Statistical Society, Series C, doi: 10.1111/rssc.12154. Vol. 65, pp. 775-795.
  18. PIERRI F., STANGHELLINI E., BISTONI N. (2016). “Risk analysis and retrospective unbalanced data”. REVSTAT, 14, Vol. 2, pp. 157-169.
  19. ALLMAN E.S., RHODES J. A., STANGHELLINI E., VALTORTA M. (2014). “Parameter identifiability of Discrete Bayesian Networks with Hidden Variables”. Journal of Causal Inference, doi: 10.1515/jci-2014-0021. Electronic Journal.
  20. STANGHELLINI E., PAKPAHAN E. (2014). “Identification of Causal Effects in Linear Models: beyond Instrumental Variables”. TEST, 24, Vol. 3, pp.489-509, doi: 10.1007/s11749-014-0421-3.
  21. GENBÄCK, M., STANGHELLINI E., DE LUNA X. (2014). “Uncertainty Intervals for regression parameters with non-ignorable missingness in the outcome”. Statistical Papers, 56, Vol. 3, pp. 829-847, doi: 10.1007/s00362-014-0610-x.
  22. NICOLOSI M., GRASSI S., STANGHELLINI E. (2014). “Item Response Models to Measure Corporate Social Responsibility”. Applied Financial Economics, 24, Vol. 22, pp.1449-1464, doi: 10.1080/09603107.2014.925070.
  23. PIERRI F., BURCHI A., STANGHELLINI E. (2013). “La capacità predittiva degli indicatori di bilancio: un metodo per le PMI”.  Piccola Impresa/Small Business, Vol 1, pp. 85-108 (in Italian).
  24. STANGHELLINI E., VANTAGGI B. (2013). “On the identification of discrete concentration graph models with one hidden binary variable ”. Bernoulli, 19, Number 5A, 1920-1937, doi:  10.3150/12-BEJ435.5.
  25. STANGHELLINI E. (2012). Contribution to the Discussion to the paper of Wermuth N. and Sadeghi K. “Sequences of regressions and their independences”, TEST, vol. 21, p. 265-267, doi: 10.1007/s11749-012-0287-1.
  26. STINGO F.C., STANGHELLINI E., CAPOBIANCO R. (2011). “On the estimation of a binary response model in a selected population”. Journal of Statistical Planning and Inference, 141, pp. 3293-3303, doi:10.1016/j.jspi.2011.04.014.
  27. HUTTON J.L., STANGHELLINI E. (2011). “Modelling bounded health scores with censored skew-normal distributions”. Statistics in Medicine, 30, pp. 368–376, doi: 10.1002/sim.4104.
  28. FORCINA A., GIOVAGNOLI A., STANGHELLINI E. (2011). “Non-compliance in surgical patients with herniated lumbar discs: an application of an extended latent class model as a selection model”. Statistical Modelling, 11(4), pp. 311-324, doi: 10.1177/1471082X1001100402.
  29. FALOCCI N., PANICCIA’ R., STANGHELLINI E. (2009). “Regression modelling of the flows in an input-output table with accounting constraints”. Statistical Papers, 50, pp. 373-382.
  30. GIORGI ROSSI. P., MANTOVANI J., FERRONI J., FORCINA A., STANGHELLINI E., CURTALE F., BORGIA P. (2009). “Bacterial meningitis surveillance in Lazio, Italy: a system integrating laboratory specificity to hospitalization database sensitivity”. BMC Infectious Diseases, 9.
  31. MARCHETTI, G.M., STANGHELLINI, E. (2008), " A note on distortions induced by truncation, with application to linear regression systems". Statistics & Probability Letters, 78, pp.824-829.
  32. WERMUTH N., STANGHELLINI E. (2006). Contribution to the Discussion to the paper of Castelo R. e Roverato. A. “A robust procedure for Gaussian graphical model search from microarray data with p lager than n”. Statistica, 66, pp. 366-368.
  33. STANGHELLINI E. (2006). “On Statistical Issues raised by the New Capital Accord”. Statistica Applicata, 18, 2, pp. 389-405.
  34. STANGHELLINI, E. , WERMUTH, N. (2005)," On the identification of path analysis models with one hidden variable". Biometrika, 92, 2, pp. 337-350.
  35. STANGHELLINI E., VAN DER HEIJDEN P.G.M. (2004). “A multiple-record systems estimation method that takes observed and unobserved heterogeneity into account”. Biometrics, 60, pp. 510-516.
  36. STANGHELLINI E. (2004). “Instrumental variables in Gaussian directed acyclic graph models with an unobserved confounder”. Environmetrics, 15, pp. 463-469.

 

Books or chapters in books (since 2004)

  1. FASANO E., GUARDABASCIO B., STANGHELLINI E. (2023) The Role of ESG on Credit Rating in the Banking Sector: A Mediation Analysis to Disentangle the Direc and Indirect Effects, in ESG Integration and SRI Strategies in the EU, Palgrave Macmillan. 10.1007/978-3-031-36457-0_8
  2. STANGHELLINI E. (2018) “Strategie della ricerca. Una introduzione”. In Cimmino L., Fanò L. Petrillo C., Santambrogio A., Stanghellini E., Veronesi F. (Eds.) Fare Scienza oggi, Vol. 2 Atti dei Convegni Interdipartimentali Università degli Studi di Perugia, Morlacchi Editore U.P. ISBN: 788860749581.
  3. STANGHELLINI E., RANALLI M.G. (2017) “Population size estimation using a categorical latent variable”. In Boehning D., Bunge J., van der Heijden P.G. Capture-Recapture Methods for the Social and Medical Sciences. Chapmand and Hall. ISBN: 9781498745314.
  4. MEALLI F., PACINI B., STANGHELLINI E. (2014). “Identification of principal causal effects using secondary outcomes”. In Carpita M., Brentari e. Qannari E. Advances in Latent Variables. Studies in Theoretical and Applied Statistics. Springer-Verlag, doi: 10.1007/10104_2014_15.
  5. GOTTARD A., STANGHELLINI E., CAPOBIANCO R. (2013). “Semicontinuous regression models with Skew distributions”. In: Grigoletto M., Lisi F., Petrone S.. Complex Models and Computational Methods in Statistics. Springer Verlag, ISBN: 9788847028708, doi: 10.1007/978-88-470-2871-5-12.
  6. STANGHELLINI E. (2009). Introduzione ai metodi statistici per il Credit Scoring. Springer Italia. ISBN: 9788847010802.
  7. FORCINA A. STANGHELLINI E. (2005). Elementi di Statistica per economia, Morlacchi Editore, Perugia (Textbook).