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An association model for bivariate data with application to the analysis of university students' success

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  • Marco Enea
  • Massimo Attanasio

Abstract

The academic success of students is a priority for all universities. We analyze the students' success at university by considering their performance in terms of both ‘qualitative performance’, measured by their mean grade, and ‘quantitative performance’, measured by university credits accumulated. These data come from an Italian University and concern a cohort of students enrolled at the Faculty of Economics. To jointly model both the marginal relationships and the association structure with covariates, we fit a bivariate ordered logistic model by penalized maximum likelihood estimation. The penalty term we use allows us to smooth the association structure and enlarge the range of possible parameterizations beyond that provided by the usual Dale model. The advantages of our approach are also in terms of parsimony and parameter interpretation, while preserving the goodness of fit.

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  • Marco Enea & Massimo Attanasio, 2016. "An association model for bivariate data with application to the analysis of university students' success," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(1), pages 46-57, January.
    • Handle: RePEc:taf:japsta:v:43:y:2016:i:1:p:46-57
    DOI: 10.1080/02664763.2014.998407
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    Cited by:

    1. Marco Centoni & Vieri Del Panta & Antonello Maruotti & Valentina Raponi, 2019. "Concomitant-Variable Latent-Class Beta Inflated Models to Assess Students’ Performance: An Italian Case Study," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 7-18, November.
    2. Contini, Dalit & Salza, Guido, 2020. "Too few university graduates. Inclusiveness and effectiveness of the Italian higher education system," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).

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