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A fuzzy set theory based computational model to represent the quality of inter-rater agreement

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  • Enrico Ciavolino
  • Sergio Salvatore
  • Antonio Calcagnì

Abstract

In this paper we present a method to evaluate the quality of a rater’s judgement, which can integrate and enrich the use of inter-rater agreement as a reliability measure. Our proposal is an integrative one and evaluates the quality of a rater’s performance through an analysis of the profile of that individual rater’s performance. We discuss its rationale on the basis of the interpretation of inter-rater agreement, highlighting some critical issues. For this purpose, we adopt a computational model based on fuzzy set theory, demonstrating its main characteristics with an exemplary case study. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Enrico Ciavolino & Sergio Salvatore & Antonio Calcagnì, 2014. "A fuzzy set theory based computational model to represent the quality of inter-rater agreement," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(4), pages 2225-2240, July.
    • Handle: RePEc:spr:qualqt:v:48:y:2014:i:4:p:2225-2240
    DOI: 10.1007/s11135-013-9888-3
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    References listed on IDEAS

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    1. Coppi, Renato & Gil, Maria A. & Kiers, Henk A.L., 2006. "The fuzzy approach to statistical analysis," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 1-14, November.
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    1. Enrico Ciavolino & Antonio Calcagnì, 2014. "A generalized maximum entropy (GME) approach for crisp-input/fuzzy-output regression model," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 3401-3414, November.

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