Abstract
The methodologies adopted in the last decades to analyze students’ university careers using cohort studies focus mainly on the risk to observe one of the possible competing states, specifically dropout or graduation, after several years of follow-up. In this perspective all the other event types that may prevent the occurrence of the target event are treated as censored observations. A broader analysis of students’ university careers from undergraduate to postgraduate status reveals that several competing and noncompeting events may occur, some of which have been denoted as absorbing while others as intermediate. In this study we propose to use multistate models to analyze the complexity of students’ careers and to assess how the risk to experience different states varies along the time for students’ with different profiles. An application is provided to show the usefulness of this approach.
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Sulis, I., Giambona, F., Tedesco, N. (2015). Using Discrete-Time Multistate Models to Analyze Students’ University Pathways. In: Morlini, I., Minerva, T., Vichi, M. (eds) Advances in Statistical Models for Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-319-17377-1_25
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DOI: https://doi.org/10.1007/978-3-319-17377-1_25
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