For the complete and updated list of pubblications check CV or visit:
https://orcid.org/0000-0002-1076-9249 Fabrizia Mealli - Google Scholar
Grossi G., Mariani M., Mattei A., Mealli F. (2025) Bayesian principal stratification with longitudinal data and truncation by death, forthcoming in Econometrics and Statistics.
Forastiere L., Mattei A., Mealli F., (2024) Selecting Subpopulations for Causal Inference in Regression Discontinuity Designs, forthcoming in Annals of Applied Statistics, https://arxiv.org/abs/2211.09099
Zigler C., Mealli F., Liu V., Forastiere L. (2024) Bipartite Interference and Air Pollution Transport: Estimating Health Effects of Power Plant Interventions, forthcoming in Biostatistics.
Comment L., Mealli F. Haneuse S., Zigler C.M.(2024) Survivor average causal effects for continuous time: a principal stratification approach to causal inference with semicompeting risks, forthcoming in Biometrical Journal, https://arxiv.org/abs/1902.09304.
Mattei A., Ding P., Ballerini V., Mealli F. (2024) Assessing causal effects in the presence of treatment switching through principal stratification, online first, Bayesian Analysis, https://doi.org/10.1214/24-BA1425.
Noirjean S., Mattei A., Mariani M., Mealli F. (2024) Exploiting Network Information to Disentangle Spillover Effects in a Field Experiment on Teens’ Museum Attendance, online first, Journal of Educational and Behavioral Statistics, https://doi.org/10.3102/10769986241254351.
Tortù C., Crimaldi I., Mealli F., Forastiere L. (2024) Estimating causal effects of multi-valued treatments accounting for network interference : immigration policies and crime rates, Sociological methods & research, Vol. 53, No. 4, pp. 1591-2045
Mealli F. , Mortimer J.H. (2024) A conversation with Guido W. Imbens, Statistical Science, 39(2): 357-373.
Wang, C, Zhang Y, Mealli, F., Bornkamp, B. (2023) Sensitivity analyses for the principal ignorability assumptions using multiple imputation. Pharmaceutical Statistics. 2023; 22 (1): 64-78. https://doi.org/10.1002/pst.2260
Li F., Ding P., Mealli F. (2023), Bayesian Causal Inference: A Critical Review, Philosophical Transactions A, Vol. 381, No. 2247, Art. 20220153, https://doi.org/10.1098/rsta.2022.0153.
Menchetti F., Cipollini, F., Mealli F., (2023) Combining counterfactual outcomes and ARIMA models for policy evaluation, The Econometrics Journal, Vol. 26, No. 1, pp. 1-24 https://doi.org/10.1093/ectj/utac024
Papadogeorgou G., Menchetti F., Choirat C., Wasfy J.H., Zigler C. M., Mealli F. (2023) Evaluating federal policies using Bayesian time series models: estimating the causal impact of the hospital readmissions reduction program, Health Services and Outcomes Research Methodology, 1-19, https://doi.org/10.1007/s10742-022-00294-8.