Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)

fIRTree: An Item Response Theory Modeling of Fuzzy Rating Data

Authors
Antonio Calcagnì
Corresponding Author
Antonio Calcagnì
Available Online 30 August 2021.
DOI
https://doi.org/10.2991/asum.k.210827.062How to use a DOI?
Keywords
Fuzzy rating scale, Rating data, Item response theory, Decision uncertainty
Abstract

In this contribution we describe a novel procedure to represent uncertainty in rating scales in terms of fuzzy numbers. Following the rationale of fuzzy conversion scale, we adopted a two-step procedure based on a psychometric model (i.e., Item Response Theory-based tree) to represent the process of answering survey questions. This provides a coherent context where fuzzy numbers, and the related fuzziness, can be interpreted in terms of decision uncertainty that usually affects the rater’s response process. We reported results from a simulation study and an empirical application to highlight the characteristics and properties of the proposed approach.

Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Cite this article

TY  - CONF
AU  - Antonio Calcagnì
PY  - 2021
DA  - 2021/08/30
TI  - fIRTree: An Item Response Theory Modeling of Fuzzy Rating Data
BT  - Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)
PB  - Atlantis Press
SP  - 471
EP  - 477
SN  - 2589-6644
UR  - https://doi.org/10.2991/asum.k.210827.062
DO  - https://doi.org/10.2991/asum.k.210827.062
ID  - Calcagnì2021
ER  -