Prof. Giorgio Vittadini is a Full Professor at the University of Milano-Bicocca where he teaches Multivariate Analysis, Data Analysis, Latent Models. His research interests concern Latent and Mixture Models, Human Capital, Health Econometrics. He organized several international meetings in connection with important international journals and participated to international projects on Health econometrics. He is author of 94 publications (44 in international journals with impact factor) with 26.51 Research GATE , che è superiore all' 80% dei ricercatori di tutto il mondo;20 h-index google scholar con 35 i10-index ; 13 Scopus h-index , 17 H-index Web of Science
Viaggio nelle Character Skills. Persone, relazioni, valori, 2021
The book addresses the issue of knowledge and learning in the school and work environment, consid... more The book addresses the issue of knowledge and learning in the school and work environment, considered as a process that involves not only cognitive skills, such as remembering, speaking, understanding, establishing connections, deducing, evaluating, but also involves transversal qualities, personality dispositions called character skills, such as open-mindedness, the ability to collaborate, confidence. The title, Journey into Character Skills. People, relationships, values, expresses the approach we intend to give to the work, which does not intend to propose statements of principle, but wants to embark on an exploratory journey in which the reflections developed by a group of scholars from various backgrounds and different skills converge. The contributions suggest the multiple perspectives with which to approach character skills in order to have a full understanding of them, just as when we travel we can look at the natural landscape and the works of man from different points of view so as to get a broader idea of what they are and what they mean. This is a journey that we would like to take with the reader around the future of education and schools. And beyond.
The cluster-weighted model (CWM) is a member of the family of mixture of regression models and is... more The cluster-weighted model (CWM) is a member of the family of mixture of regression models and is also known as mixtures of regressions with random covariates. CWMs refer to the framework of model-based clustering and have their natural application when the research interest requires modeling the relationship between a response variable and a set of covariates using a regressionbased approach such as a generalized linear model and the sample is suspected to be composed by heterogeneous latent classes. Software for estimating these models is not yet available in Stata. The aim of this article is to introduce the Stata package cwmglm, which allows fitting CWMs based on the most common generalized linear models with random covariates. Moreover, cwmglm allows the estimation of parsimonious models of Gaussian distributions, with the parametrization of the variance-covariance matrix based on the eigenvalue decomposition. These features are completely new for Stata users. The cwmglm package features goodness-of-fit, bootstrapping and model selection tools. We illustrate the use of cwmglm with real and simulated datasets.
ABSTRACT The language of abstract vector spaces is used to show that the latent variables and err... more ABSTRACT The language of abstract vector spaces is used to show that the latent variables and errors of the Lisrel model can always be constructed so as to predict any criterion perfectly,including all those that are entirely uncorrelated with the observed variables.
The latent variables and errors of the Lisrel model are indeterminate even when the parameters of... more The latent variables and errors of the Lisrel model are indeterminate even when the parameters of the model are perfectly identified. The reason for the indeterminacy is that the Lisrel model gives a solution in terms of estimation of latent variables by means of observed variables. The indeterminacy is relevant also in practice; the minimum correlation between equivalent latent variables, is often negative in empirical examples. The degree of indeterminacy of the latent variables depends on the data. The average minimum correlation is a linear combination of the eigenvalues of the correlation matrix of solutions and it is always included in weak bounds which depend on the same eigenvalues.
Studies in classification, data analysis, and knowledge organization, Nov 25, 2009
ABSTRACT We propose a general methodology for evaluating the quality of public sector activities ... more ABSTRACT We propose a general methodology for evaluating the quality of public sector activities such as education, health and social services. The traditional instrument used in comparisons of institutional performance is Multilevel Modeling (Goldstein, H., Multilevel statistical models, Arnold, London, 1995). However, rankings based on confidence intervals of the organization-level random effects often prevent to discriminate between institutions, because uncertainty intervals may be large and overlapped. This means that, in some situations, a single global model is not sufficient to explain all the variability, and methods able to capture local behaviour are necessary. The proposal, which is entitled Local Multilevel Modeling, consists of a two-step approach which combines Cluster-Weighted Modeling (Gershenfeld, N., The nature of mathematical modeling, Cambridge University Press, Cambridge, 1999) with traditional Multilevel Modeling. An example regarding the evaluation of the “relative effectiveness” of healthcare institutions in Lombardy region is discussed.
Viaggio nelle Character Skills. Persone, relazioni, valori, 2021
The book addresses the issue of knowledge and learning in the school and work environment, consid... more The book addresses the issue of knowledge and learning in the school and work environment, considered as a process that involves not only cognitive skills, such as remembering, speaking, understanding, establishing connections, deducing, evaluating, but also involves transversal qualities, personality dispositions called character skills, such as open-mindedness, the ability to collaborate, confidence. The title, Journey into Character Skills. People, relationships, values, expresses the approach we intend to give to the work, which does not intend to propose statements of principle, but wants to embark on an exploratory journey in which the reflections developed by a group of scholars from various backgrounds and different skills converge. The contributions suggest the multiple perspectives with which to approach character skills in order to have a full understanding of them, just as when we travel we can look at the natural landscape and the works of man from different points of view so as to get a broader idea of what they are and what they mean. This is a journey that we would like to take with the reader around the future of education and schools. And beyond.
The cluster-weighted model (CWM) is a member of the family of mixture of regression models and is... more The cluster-weighted model (CWM) is a member of the family of mixture of regression models and is also known as mixtures of regressions with random covariates. CWMs refer to the framework of model-based clustering and have their natural application when the research interest requires modeling the relationship between a response variable and a set of covariates using a regressionbased approach such as a generalized linear model and the sample is suspected to be composed by heterogeneous latent classes. Software for estimating these models is not yet available in Stata. The aim of this article is to introduce the Stata package cwmglm, which allows fitting CWMs based on the most common generalized linear models with random covariates. Moreover, cwmglm allows the estimation of parsimonious models of Gaussian distributions, with the parametrization of the variance-covariance matrix based on the eigenvalue decomposition. These features are completely new for Stata users. The cwmglm package features goodness-of-fit, bootstrapping and model selection tools. We illustrate the use of cwmglm with real and simulated datasets.
ABSTRACT The language of abstract vector spaces is used to show that the latent variables and err... more ABSTRACT The language of abstract vector spaces is used to show that the latent variables and errors of the Lisrel model can always be constructed so as to predict any criterion perfectly,including all those that are entirely uncorrelated with the observed variables.
The latent variables and errors of the Lisrel model are indeterminate even when the parameters of... more The latent variables and errors of the Lisrel model are indeterminate even when the parameters of the model are perfectly identified. The reason for the indeterminacy is that the Lisrel model gives a solution in terms of estimation of latent variables by means of observed variables. The indeterminacy is relevant also in practice; the minimum correlation between equivalent latent variables, is often negative in empirical examples. The degree of indeterminacy of the latent variables depends on the data. The average minimum correlation is a linear combination of the eigenvalues of the correlation matrix of solutions and it is always included in weak bounds which depend on the same eigenvalues.
Studies in classification, data analysis, and knowledge organization, Nov 25, 2009
ABSTRACT We propose a general methodology for evaluating the quality of public sector activities ... more ABSTRACT We propose a general methodology for evaluating the quality of public sector activities such as education, health and social services. The traditional instrument used in comparisons of institutional performance is Multilevel Modeling (Goldstein, H., Multilevel statistical models, Arnold, London, 1995). However, rankings based on confidence intervals of the organization-level random effects often prevent to discriminate between institutions, because uncertainty intervals may be large and overlapped. This means that, in some situations, a single global model is not sufficient to explain all the variability, and methods able to capture local behaviour are necessary. The proposal, which is entitled Local Multilevel Modeling, consists of a two-step approach which combines Cluster-Weighted Modeling (Gershenfeld, N., The nature of mathematical modeling, Cambridge University Press, Cambridge, 1999) with traditional Multilevel Modeling. An example regarding the evaluation of the “relative effectiveness” of healthcare institutions in Lombardy region is discussed.
The indeterminacy of the Structural Models, i.e. the arbitrariness of latent scores, due to the f... more The indeterminacy of the Structural Models, i.e. the arbitrariness of latent scores, due to the factorial nature of the measurement models, is, in the dynamic context, more problematic. We propose an alternative formulation of the Structural Dynamic Model, based on the Replicated Common Factor Model (Haagen e Oberhofer, 1999), where latent scores are no more indeterminate.
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