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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Suleman, A. (2017). A fuzzy clustering approach to evaluate individual competencies from REFLEX data. Journal of Applied Statistics. 44 (14), 2513-2533
Exportar Referência (IEEE) 
A. K. Suleman,  "A fuzzy clustering approach to evaluate individual competencies from REFLEX data", in Journal of Applied Statistics, vol. 44, no. 14, pp. 2513-2533, 2017
Exportar BibTeX 
@article{suleman2017_1714141968106,
	author = "Suleman, A.",
	title = "A fuzzy clustering approach to evaluate individual competencies from REFLEX data",
	journal = "Journal of Applied Statistics",
	year = "2017",
	volume = "44",
	number = "14",
	doi = "10.1080/02664763.2016.1257589",
	pages = "2513-2533",
	url = "http://www.tandfonline.com/loi/cjas20"
}
Exportar RIS 
TY  - JOUR
TI  - A fuzzy clustering approach to evaluate individual competencies from REFLEX data
T2  - Journal of Applied Statistics
VL  - 44
IS  - 14
AU  - Suleman, A.
PY  - 2017
SP  - 2513-2533
SN  - 0266-4763
DO  - 10.1080/02664763.2016.1257589
UR  - http://www.tandfonline.com/loi/cjas20
AB  - 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.
ER  -