A multivariate multilevel model for the analysis of graduates’ skills

The aim of the paper is to analyze some of the data gathered by a telephone survey conducted, about two years after the degree, on the 2000’s graduates of the University of Florence. The main goal is to determine the factors which influence the way of acquisition of the skills and to evaluate the degree programmes on the basis of the adequacy of the skills they give to their graduates. The analysis of such data raises several methodological questions. In order to taking into account the features of the data, a suitable multivariate multilevel model for polytomous responses with a non-ignorable missing data mechanism is developed and fitted by means of maximum likelihood with adaptive Gaussian quadrature. In the application the multilevel structure has a crucial role, while selection bias results negligible. The analysis of the empirical Bayes residuals allows to detect some extreme degree programmes to be further inspected.