A fuzzy clustering approach to evaluate individual competencies from REFLEX data

Abdul Suleman

Journal of Applied Statistics, 2017, vol. 44, issue 14, 2513-2533

Abstract: We empirically illustrate how concepts and methods involved in a grade of membership (GoM) analysis can be used to sort individuals by competence. Our study relies on a data set compiled from the international survey on higher education graduates called REFLEX. We focus on the subset of data related to the perception of own competencies. It is first decomposed into fuzzy clusters that form a hierarchical fuzzy partition. Then, we calculate a scalar measure of competencies for each fuzzy cluster, and subsequently use the individual GoM scores to combine cluster-based competencies to position individuals on a scale from 0 to 1.

Date: 2017
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DOI: 10.1080/02664763.2016.1257589

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