Employment status and education/employment relationship of PhD graduates from the University of Ferrara

Rosa Arboretti Giancristofaro, Stefano Bonnini and Luigi Salmaso

Journal of Applied Statistics, 2009, vol. 36, issue 12, 1329-1344

Abstract: Two sample surveys of Post-Docs were planned and carried out at the University of Ferrara in 2004 and 2007 aimed at determining the professional status of Post-Docs, the relationship between their PhD education and employment, and their satisfaction with certain aspects of the education and research program. As part of these surveys, two methodological contributions were developed. The first concerns an extension of the non-parametric combination of dependent rankings to construct a synthesis of composite indicators measuring satisfaction with particular aspects of PhD programs [R. Arboretti Giancristofaro and L. Salmaso, Global ranking indicators with application to the evaluation of PhD programs, Atti del Convegno “Valutazione e Customer Satisfaction per la Qualita dei Servizi”, Roma, 8-9 Settembre 2005, pp. 19-22; R. Arboretti Giancristofaro, S. Bonnini, and L. Salmaso, A performance indicator for multivariate data, Quad. Stat. 9 (2007), pp. 1-29; R. Arboretti Giancristofaro, F. Pesarin, and L. Salmaso, Nonparametric approaches for multivariate testing with mixed variables and for ranking on ordered categorical variables with an application to the evaluation of PhD programs, in Real Data Analysis, S. Sawilowsky, ed., a volume in Quantitative Methods in Education and the Behavioral Sciences: Issues, Research and Teaching, Ronald C. Serlin, series ed., Information Age Publishing, Charlotte, North Carolina, 2007, pp. 355-385]. The procedure was applied to highlight differences in the interviewed Post-Docs' multivariate satisfaction profiles in relation to two aspects: education/employment relationship; employment expectations; and opportunities. The second consists of an inferential procedure providing a solution to the problem of hypothesis testing, where the objective is to compare the heterogeneity of two populations on the basis of sampling data [G.R. Arboretti, S. Bonnini, and F. Pesarin, A permutation approach for testing heterogeneity in two-sample categorical variables, Stat. Comput. (2009) doi: 10.1007/S11222-008-9085-8.]. The procedure was applied to compare the degrees of heterogeneity of Post-Doc judgments in the two surveys with regard to the adequacy of the PhD education for the work carried out.

Keywords: employment survey; performance indicators; heterogeneity tests (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (3)

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DOI: 10.1080/02664760802638108

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