| Comparative analysis of alcohol control policies in 30 countries DA Brand, M Saisana, LA Rynn, F Pennoni, AB Lowenfels PLoS medicine 4 (4), e151, 2007 | 389 | 2007 |
| Latent Markov models for longitudinal data F Bartolucci, A Farcomeni, F Pennoni CRC Press, 2012 | 374 | 2012 |
| LMest: An R package for latent Markov models for longitudinal categorical data F Bartolucci, S Pandolfi, F Pennoni Journal of Statistical Software 81, 1-38, 2017 | 99 | 2017 |
| Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates F Bartolucci, A Farcomeni, F Pennoni Test 23, 433-465, 2014 | 97 | 2014 |
| The causal effects of parental divorce and parental temporary separation on children’s cognitive abilities and psychological well-being according to parental relationship quality A Garriga, F Pennoni Social Indicators Research 161 (2), 963-987, 2022 | 84 | 2022 |
| A latent Markov model for detecting patterns of criminal activity F Bartolucci, F Pennoni, B Francis Journal of the Royal Statistical Society Series A: Statistics in Society 170 …, 2007 | 81 | 2007 |
| A comparison of some criteria for states selection in the latent Markov model for longitudinal data S Bacci, S Pandolfi, F Pennoni Advances in Data Analysis and Classification 8, 125-145, 2014 | 77 | 2014 |
| Assessment of school performance through a multilevel latent Markov Rasch model F Bartolucci, F Pennoni, G Vittadini Journal of Educational and Behavioral Statistics 36 (4), 491-522, 2011 | 60 | 2011 |
| Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations K Sherratt, H Gruson, H Johnson, R Niehus, B Prasse, F Sandmann, ... Elife 12, e81916, 2023 | 58 | 2023 |
| Exploiting TIMSS and PIRLS combined data: multivariate multilevel modelling of student achievement L Grilli, F Pennoni, C Rampichini, I Romeo | 56 | 2016 |
| Longitudinal analysis of self-reported health status by mixture latent auto-regressive models F Bartolucci, S Bacci, F Pennoni Journal of the Royal Statistical Society Series C: Applied Statistics 63 (2 …, 2014 | 49 | 2014 |
| An overview of latent Markov models for longitudinal categorical data F Bartolucci, A Farcomeni, F Pennoni arXiv preprint arXiv:1003.2804, 2010 | 37 | 2010 |
| A class of latent Markov models for capture–recapture data allowing for time, heterogeneity, and behavior effects F Bartolucci, F Pennoni Biometrics 63 (2), 568-578, 2007 | 36 | 2007 |
| Causal latent Markov model for the comparison of multiple treatments in observational longitudinal studies F Bartolucci, F Pennoni, G Vittadini Journal of Educational and Behavioral Statistics 41 (2), 146-179, 2016 | 25 | 2016 |
| Issues on the estimation of latent variable and latent class models F Pennoni Scholars' Press, 2014 | 23 | 2014 |
| The 2005 European e-business readiness index F Pennoni, S Tarantola, A Latvala | 21 | 2006 |
| NEETs and youth unemployment: A longitudinal comparison across European countries F Pennoni, B Bal-Domańska Social Indicators Research 162 (2), 739-761, 2022 | 19 | 2022 |
| Studying enhanced recovery after surgery (ERAS®) core items in colorectal surgery: a causal model with latent variables M Gemma, F Pennoni, M Braga World journal of surgery 45 (4), 928-939, 2021 | 18 | 2021 |
| Discrete latent variable models F Bartolucci, S Pandolfi, F Pennoni Annual Review of Statistics and Its Application 9 (1), 425-452, 2022 | 15 | 2022 |
| LMest: an R package for latent Markov models for categorical longitudinal data F Bartolucci, A Farcomeni, S Pandolfi, F Pennoni arXiv preprint arXiv:1501.04448, 2015 | 15 | 2015 |
Stefano TarantolaJoint Research Centre, European Commissionכתובת אימייל מאומתת בדומיין jrc.ec.europa.eu