Quantitative Methods Research: Efficiency and Regression Mixtures Analysis

DEPARTMENT OF STATISTICS AND QUANTITATIVE METHODS RESEARCH 1

EFFICIENCY (VITTADINI) TIME INVARIANT INEFFICIENCY TIME VARIANT INEFFICIENCY SPECIFIC INEFFICIENCY THREE KINDS INEFFICIENCY MODELS 2

Colombi R., Kumbhakar S., Martini G.M., Vittadini G. (2014) Closed-Skew Normality in Stochastic Frontiers with Individual Effects and Long/Short Run Efficienty, Journal of Productivity Analysis, 2, 123-136. Colombo R., Martini G., Vittadini G. (2017) Determinants of transient and persistent hospital efficiency: The case of Italy, Health Economics, Volume 26, Issue Supplement S2, Pages 5 22. ON GOING Martini G, Scotti D, Viola D., Vittadini G. Persistent and Temporary Inefficiency in Airport Cost Function: An Application to Italy, ATRS Special Issue 3

REGRESSION MIXTURES (LOVAGLIO, BERTA,GRESELIN,MINOTTI, PENNONI, VITTADINI) MIXTURE MODELING CLUSTER WEIGHTED MODEL MODEL-BASED CLASSIFICATION ROBUST CLUSTERING MIXTURES OF FACTOR ANALYZERS 4

Ingrassia S., Punzo A., Vittadini G., Minotti S. (2015) The Generalized Linear Mixed Cluster-Weighted Model, Journal of Classification, 32, 85-113. Berta P., Ingrassia S., Punzo A., Vittadini G. (2016). Multilevel cluster-weighted models for the evaluation of hospitals. METRON, pages 1 18, 2016 Garci a-Escudero L.A., Gordaliza A., Greselin F., Ingrassia S., Mayo-Iscar A., 2017, Robust estimation of mixtures of regressions with random covariates, via trimming and constraints, Statistics and Computing, 27, 2, 377-402 Garci a-Escudero L.A., Greselin F., Mayo-Iscar A., 2018, Robust fuzzy and parsimonious clustering based on mixtures of Factor Analyzers, International Journal of Approximate Reasoning, 94, 60-75 5

Garcia-Escudero L.A., Gordaliza A., Greselin F., Ingrassia S., Mayo-Iscar A., 2018, Eigenvalues and constraints in mixture modeling: geometric and computational issues, Advances in Data Analysis and Classification, 12, 2, 203-233. Berta P. and Vinciotti V. (2019). Multilevel logistic cluster-weighted model for outcome evaluation in healthcare. Statistical Analysis and Data Mining . Cappozzo A., Greselin F., Murphy B., 2019, A robust approach to model-based classification based on trimming and constraints. Advances in Data Analysis and Classification, Online First, 28 pages, 6

STATISTICAL ANALYSIS OF MULTIDIMENSIONAL ORDINAL DATA (FATTORE) PARTIALLY ORDERED STRUCTURES CONSTRUCTION OF SYNTHETIC INDICATORS ALGORITHMS FOR THE ANALYSIS OF MULTIDIMENSIONAL ORDINAL DATA DEVELOPMENT OF SOFTWARE RESOURCES 7

Fattore M. (2017) Functionals and synthetic indicators over finite posets, In M. Fattore, R. Bruggemann (eds.), Partial Order Concepts in Applied Sciences, Springer Fattore M. (2017) Synthesis of indicators: the non-aggregative approach , In F. Maggino (ed.), Complexity in societies: From Indicators Construction to their Synthesis, Springer. Fattore M. (2018) Partially Ordered Sets , Wiley StatsRef: Statistics Reference Online, John Wiley & Sons, Ltd. 8

BIG DATA, MACHINE LEARNING (ARMANI,BOSELLI CESARINI, FATTORE, GRESELIN,LOVAGLIO, MALANDRI,MERCORIO, MEZZANZANICA, SOLARO) BUSINESS INTELLIGENCE AND DECISION MAKING BIG DATA ANALYTICS AND DATA PROCESSING KNOWLEDGE DISCOVERY IN DATABASES MACHINE LEARNING / DATA MINING . IMPUTATION DATA METHODS IMPUTING MISSING DATA 9

Grassi R., Fattore M., Arcagni A. (2015) Structural and non-structural temporal evolution of socio-economic real networks , Quality and Quantity 49, pp. 1597-1608 Mezzanzanica M., Mercorio F., Boselli F., Malandri L., Armani M. (2015).A model-based evaluation of data quality activities in KDD. Inf. Process. Manage. 51(2) Solaro N.,Barbiero A.,Manzi G.,Ferrari P. (2017).A sequential distance-based approach for imputing missing data: Forward Imputation, Advances in Data Analysis and Classification,11,395 -414, Berta P., Bossi M., Verzillo S. (2017).%CEM: a SAS macro to perform Coarsened Exact Matching. Journal of Statistical Computation and Simulation, 87(2):227 238 Clemente G. P.,Fattore M.,Grassi R.(2018) Structural comparisons of networks and model-based detection of small-worldness,Journal of Economic Interaction and Coordination-13(1), 117 -141 Solaro N., Barbiero A., Manzi G., Ferrari P.A. (2018). A simulation comparison of imputation methods for quantitative data in the presence of multiple data patterns, Journal of Statistical Computation and Simulation, 88(18), 3588-3619 10

Lovaglio P.G., Cesarini M., Mercorio F., Mezzanzanica M. (2018) Skills in demand for ICT and statistical occupations: evidences from web vacancies. Statistical Analysis and Data Mining Fattore M. (2018) Machine learning , Wiley StatsRef: Statistics Reference Online. Mezzanzanica M., Mercorio F., Boselli F., Malandri L., Armani M.(2019). MAI meets labor market: Exploring the link between automation and skills. Information Economics and Policy.47 Mezzanzanica M., Mercorio F., Boselli F., Malandri L., Armani M.(2019). GraphDBLP: a system for analysing networks of computer scientists through graph databases. Multimedia Tools Appl. 77(14) Greselin F., Piacenza F., Zitikis R., 2019, Practice Oriented and Monte Carlo Based Estimation of the Value-at-Risk for Operational Risk Measurement. Risks, 7(2):50, 11

LATENT VARIABLES- CAUSAL MODELS (LOVAGLIO, BERTA, GRESELIN, PENNONI, VITTADINI) STRUCTURAL EQUATION MODELS (SEM) PARTIAL LEAST SQUARES MODELS COMPONENT ANALYSIS MODELS SEM UNIQUENESS: IDENTIFICATION-INDETERMINACY LATENT MARKOV MODELS CAUSAL INFERENCE 12

. Lovaglio P.G., Boselli, R. (2015) Simulation studies of structural equation models with covariates in a redundancy analysis framework, Quality & Quantity49(3), pp. 881-890 Lovaglio P.G., Vacca, G. (2016) ERA: A SAS Macro for extended redundancy analysis. Journal of Statistical Software 74-CS1. Pennoni, F., Romeo I. (2016). Latent Markov and growth mixture models for ordinal individual responses with covariates: A comparison. Statistical Analysis and Data Mining, 1-11, Garci a-Escudero L.A., Gordaliza A., Greselin F., Ingrassia S., Mayo-Iscar A., 2016, The joint role of trimming and constraints in robust estimation of Gaussian factor analyzers, Computational Statistics and Data Analysis, 99, 131-147. 13

Bartolucci, F., Pennoni, F. Vittadini, G. (2016). Causal latent Markov model for the comparison of multiple treatments in observational longitudinal studies, Journal of Educational and Behavioral Statistics, 41, 146-179 Lovaglio P.G., Vacca, G. (2017) %GRA: A SAS macro for generalized redundancy analysis. Journal of Statistical Computation and Simulation 87(5), pp.1048 1060. Bartolucci, F., Pandolfi, S., Pennoni, F. (2017). LMest: An R package for latent Markov models for longitudinal categorical data, 1-38, Journal of Statistical Software, 81, 1-38 Fattore M., Pelagatti M., Vittadini G. (2018) A least squares approach to latent variables extraction in formative-reflective models , Computational Statistics and Data Analysis 120, 84- 97. 14

Pennoni, F. Genge E. (2019). Analysing the course of public trust via hidden Markov models: a focus on the Polish society, Statistical Methods & Applications, 1-27, Online first Pennoni, F., Nakai, M. (2019). A latent class analysis towards stability and changes in breadwinning patterns among coupled households. Dependence Modeling, 7, 234-246 Bartolucci, F., Pennoni, F. (2019). Comment on: The class of CUB models: statistical foundations, inferential issues and empirical evidence, Statistical Methods and Applications, 1-4, ON GOING Vacca, G., Lovaglio P. Redundancy Analysis Models with Categorical Endogenous Variables: A New Estimation Technique Based on Artificial Neural Networks -Vacca, G., Lovaglio P. Component analysis with categorical endogenous variables: A new estimation technique based on vector GLM 15

HEALTH ECONOMETRICS (LOVAGLIO, BERTA, SOLARO, VITTADINI) EFFECTIVENESS EFFICIENCY PATIENT CHOICE QUALITY AND COMPETITION FREE MARKET AND REGULATION PRIVATE PROFIT, NON PROFIT, PUBLIC MARKET HEALTH-SCALE VALIDATION MENTAL HEALTH HEALTH-PALLIATIVE CARE CARDIAC DISEASES 16

Martini P., Berta P., Mullahy J., Vittadini G. (2014) The Effectiveness-Efficiency Trade-Off in Health Care: The Case of Hospitals in Lombardy, Italy, Regional Science and Urban Economics, 49, November, 217 231 Berta P., Martini G., Moscone F., Vittadini G.(2016). The association between asymmetric information, hospital competition and quality of healthcare: evidence from italy. Journal of the Royal Statistical Society: Series A (Statistics in Society), 179(4):907 926,. Lucini D., Zanuso S., Solaro N., Vigo C., Malacarne M., Pagani M. (2016). Reducing the risk of metabolic syndrome at the worksite: preliminary experience with an ecological approach, Acta Diabetologica, 53, 1, 63-71 Moscone F., Tosetti E., Vittadini G. (2016) The Impact of Precarious Employment on Mental Health: the Case of Italy, Social Science & Medicine, Vol. 158, 86-95 17

Pennoni, F., Barbato, M., Del Zoppo, S. (2017). Latent Markov model with covariates to study unobserved heterogeneity among fertility patterns of couples. Frontiers in Public Health, 5, 1-9, Sala, R; Malacarne, M; Solaro, N; Pagani, M; Lucini, D (2017). A composite autonomic index as unitary metric for heart rate variability: a proof of concept, European Journal of Clinical Investigation, 47(3), 241-249 Berta P., Levaggi R., Martini G., Verzillo S.(2017). The redistributive effects of copayment in outpatient prescriptions: evidence from lombardy. BMC Health Services Research, 17(1):336, Pennoni, F., Barbato, M., Del Zoppo, S. (2017). Latent Markov model with covariates to study unobserved heterogeneity among fertility patterns of couples. Frontiers in Public Health, 5, 1-9, 18

Sala, R; Malacarne, M; Tosi, F; Benzi, M; Solaro, N; Tamorri, S; Spataro, A; Pagani, M; Lucini, D (2017). May a unitary autonomic index help assess autonomic cardiac regulation in elite athletes? Preliminary observations on the national Italian Olympic committee team, Journal of Sports Medicine and Physical Fitness, 57(12), 1702-1710 . Scaccabarozzi G., Lovaglio P.G., Limonta F., Floriani M., Pellegrini G. (2017), Quality assessment of Palliative Home Care in Italy, Journal of Evaluation in Clinical Practice, 23(4), pp. 725-733. Lovaglio, P.G. (2017) Are quality indicators predictive of compensated injury claims? Quality & Quantity 51 (4) pp. 1903-1994. Scaccabarozzi G., Lovaglio P.G., (2018) Palliative care at home: quality measurement and organizational drivers: evidences from Italy. Quality & Quantity, 22(5), 2133-2150 Vittadini G., Gianmaria Martini (2018) Administrative Dat and Health Outcome assesment: Methodology and Application, in Heath Econometrics, pp. 285-304. 19

Scaccabarozzi G., Amodio E., Pellegrini G., Limonta F., Lora Aprile P, Lovaglio P.G., Peruselli C., Crippa. M (2018) The ARIANNA project: an observational study on a model of early identification of patients with palliative care needs through the integration between Primary Care and Italian Home Palliative Care Units, Journal of Palliative Medicine, 21(5) 631-637. Tommaso Grillo Ruggieri, Paolo Berta, Anna Maria Murante, and Sabina Nuti (2018). Patient satisfaction, patients leaving hospital against medical advice and mortality in italian university hospitals: a cross-sectional analysis. BMC Health Services Research, 18(51),. Peluso A., Berta P., and Vinciotti V. (2018). Do pay-for-performance incentives lead to a better health outcome? Empirical Economics, pages 1 18,. Lucini D., Solaro N., Pagani M. (2018). Autonomic differentiation map: A novel statistical tool for interpretation of heart rate variability, Frontiers in Physiology, section Computational Physiology and Medicine , 9, 1-13, 20

Seghieri C., Berta P., Nuti S. (2019) Geographic variation in inpatient costs for acute myocardial infarction care: Insights from italy. Health Policy,. Villa G.F., Kette F., Balzarini F., Ricc M., Manera M., Solaro N., Pagliosa A., Zoli A., Migliori M., Sechi G.M., Odone A., Signorelli C. (2019). Out-of-hospital cardiac arrest (OHCA) Survey in Lombardy: data analysis through prospective short time period assessment, Acta Biomedica, Vol 90 / Suppl 9, 64-70 Solaro N., Malacarne M., Pagani M., Lucini D. (2019). Cardiac baroreflex, HRV, and statistics: an interdisciplinary approach in hypertension, Frontiers in Physiology, section Autonomic Neuroscience , 10, 1-17 ON GOING Moscone F.Siciliani L, Tosetti E., Vittadini G.Do Public and Private Hospitals differ in Quality? Evidence from Italy, Regional Studies and Urban Economics 21

EDUCATION (LOVAGLIO, BERTA, PENNONI, VITTADINI) HUMAN CAPITAL NON COGNITIVE SKILLS EDUCATION INEQUALITY HIGHER EDUCATION FAMILY EDUCATION 22

Garriga A., Sarasa S., Berta P. (2015). Mothers educational level and single motherhood: Comparing spain and italy. Demographic Research, 33:1165 1210, Grilli, L., Pennoni, F., Rampichini, C., Romeo, I. (2016). Exploiting TIMSS and PIRLS combined data: multivariate multilevel modelling of student achievement, Annals of Applied Statistics, 4, 2405-2426. Lovaglio P.G, Vacca G., Verzillo, S. (2016) Human capital estimation in higher education. Advances in Data Analysis and Classification 10(4), pp. 465-489. Lovaglio P.G., Verzillo S. (2016) Heterogeneous economic returns to higher education: evidence from Italy. Quality & Quantity 50, pp. 791-822 23

Lovaglio P., Verzillo S. Vittadini G. (2018). Social and Migration-related Inequality in Achievement in Primary and Secondary Education. In: G. Passaretta and J. Skopek (eds.), Roots and Development of Achievement Gaps. A Longitudinal Assessment in Selected European Countries, pp. 158-172, ISOTIS Report (D 1.3), Trinity College Dublin. Anna Garriga and Paolo Berta (2018). Single-mother families, mothers educational level, childrens school outcomes. In Unequal Family Lives: Causes and Consequences in Europe and the Americas, pages 143 164. Cambridge University Press . 24

LABOUR MARKET ((ARMANI,BOSELLI CESARINI, LOVAGLIO, MALANDRI,MERCORIO, MEZZANZANICA) WEB-BASED JOB VACANCIES LABOUR MARKET INTELLIGENCE SYSTEM BIG DATA AND LABOUR MARKET MACHINE LEARNING AND LABOUR MARKET 25

Mezzanzanica M., Mercorio F. , Boselli R., Malandri L. , Amami M. (2018) Skills in demand for ICT and statistical occupations: Evidence from web-based job vacancies. Statistical Analysis and Data Mining 11(2) Mezzanzanica M., Mercorio F. , Boselli R., Malandri L. , Amami M.(2018) WoLMIS: a labor market intelligence system for classifying web job vacancies. J. Intell. Inf. Syst. 51(3) Mezzanzanica M., Mercorio F. , Boselli R., Malandri L. , Amami M.(2018) Classifying online Job Advertisements through Machine Learning. Future Generation Comp. Syst. 86 Mezzanzanica M., Mercorio F. , Boselli R., Malandri L. , Amami M.(2019) Big Data Enables Labor Market Intelligence. Encyclopedia of Big Data Technologies ON GOING Lovaglio P., Colombo E., Mercorio F., Mezzanzanica M. Feature Extraction, Classification and Representativeness of Online Job Vacancies. Strategies and Empirical Evidence from Italy 26

SOCIAL STATISTICS (LOVAGLIO, BERTA, GRESELIN, PENNONI, VITTADINI) INEQUALITY STUDIES INEQUALITY MEASURES SOCIAL INDICATORS ORDINAL DATA AND CLASSIFICATION FUZZY ORDER INDICATORS WELL-BEING EVALUATION 27

Fattore M., Maggino F., (2015) A new method for measuring and analyzing suffering Comparing suffering patterns in Italian society , In R, E. Anderson (Editor) World Suffering and the Quality of Life. New York: Springer, pp. 385-400 Fattore M., Maggino F., Arcagni A. (2015) Exploiting ordinal data for subjective wellbeing evaluation , Statistics in Transition new series, Special Issue The measurement of Subjective Well-Being in Survey Research , published online April 2015 Fattore M., Maggino F., Arcagni A. (2016) Non-aggregative assessment of subjective well- being , In G. Alleva, A. Giommi (eds.), Topics in Theoretical and Applied Statistics, Springer International Publishing Switzerland Fattore M. (2017) Socio-economic statistics for a complex world: perspectives and challenges in the big data era , In F. Maggino (ed.), Complexity in societies: From Indicators Construction to their Synthesis, Springer. Fattore M., Maggino M. (2018) Some considerations on well-being evaluation procedures, taking the cue from Exploring Multidimensional Well-Being in Switzerland: Comparing Three Synthesizing Approaches , Social Indicators Research, 137(1), 83-91 28

Fattore M., Arcagni A. (2018) F-FOD: Fuzzy First Order Dominance analysis and populations ranking over ordinal multi-indicator systems , Social Indicators Research Fattore M. (2018) Non-aggregated indicators of environmental sustainability , Silesian Statistical Review, 16(22), 7-22. Davydov Y ., Greselin F., 2018,Comparisons between poorest and richest to measure inequality, Sociological Methods and Research, First Published January 9, Greselin F., Zitikis R., 2018,From the classical Gini index of income inequality to a new Zenga-type relative measure of risk: a modeller's perspective, Econometrics, 6(1), 4, Arcagni A., Barbiano di Belgiojoso E., Fattore M., Rimoldi S. (2019) Multidimensional Analysis of Deprivation and Fragility Patterns of Migrants in Lombardy, Using Partially Ordered Sets and Self-Organizing Maps , Social Indicators Research 141(2), 551 579 . 29

Fattore M., Maggino F. (2019) Social polarization, Wiley StatsRef: Statistics Reference Online Fattore M., Maggino F. (2019) Synthetic indicators for modern societies: conveying information, preserving complexity , Harmonization: Newsletter on Survey Data - Harmonization in the Social Sciences, Volume 5, Issue 1 - ISSN 2392-0858. Davydov Y., Greselin F., 2019, Inferential results for a new measure of inequality. The Econometrics Journal, 22 (2), 153-172 30

RESEARCH PROJECTS PENNONI F - 1.. EIFF 2008-2011 (Einaudi Insititute): Advances in non-linear panel data models with socio-economic applications . - 2. with Vittadini G. FIRB Futuro in Ricerca 2012 (Italian Government): Finite mixture and latent variable models for causal inference and analysis of socio- economic data. 3. STAR 2013 (European Commission): Statistics with Unobservable variables, Statistical models for human perceptions and Evaluation . 31

N.SOLARO 1. 2014-ongoing: Development of integrated statistical methodologies for the evaluation of the role of the autonomic nervous system in the context of CVD prevention through lifestyle changes . In collaboration with Daniela Lucini and Massimo Pagani, BIOMETRA Department, University of Milan, and Exercise Medicine Unit, Humanitas Clinical and Research Center, Rozzano, Italy [Topics: Multivariate Statistical Analysis, Non-parametric bootstrap, Non-parametric inference, Composite Indicators, ANS, CVD] 2. 2017-ongoing: Dissimilarity Profile Analysis: a novel exploratory tool for dissimilarity matrices . [Topics: Multivariate Statistical Analysis, Proximity Measures, Profile Analysis] 32

MEZZANZANICA AND C. 1. 2017-ongoing: Real-time Labour Market information on Skill Requirements: Setting up the EU system for online vacancy analysis . The Cedefop EU Agency [Topics: Machine Learning, Big Data Analytics, Big Data Processing, Decision Making, LMI] 2. 2018-ongoing: Big Data and Labour Market Information . European Training Foundation. [Topics: Machine Learning, Big Data Analytics, Big Data Processing, Decision Making, LMI] 3. 2019-ongoing: SLEM: A System for Smart Legal Management . MISE Italian Project [Topics: Machine Learning, NLP, NoSQL] 4. 2019-ongoing: Artificial Intelligence and Legal Studies Perspectives. Are the Algorithmic decision-making and data driven predictions calling for a new legal framework? PRIN 2018 [Topics: Machine Learning, NLP, LMI] 5. 2019-ongoing: A model for analysing the quality of tyres production . Pirelli [Topics: Machine Learning, Big Data Analytics, Data Quality] 33

BERTA P. VITTADINI G. - 1. 2014-on going Hospital evaluation in a Region Network with Mes Laboratory- S.Anna of Pisa School 2. 2017-on going Non cognitive skills, cognitive skills, education treatments in Province of Trento schools 3. 2019-on going Performance evaluation and value assessment for cardiovascular and oncological care paths in a Regional network context: challenges and opportunities Health Ministry 34