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.
fIRTree: An Item Response Theory Modeling of Fuzzy Rating Data
Calcagnì, Antonio
2021
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.File | Dimensione | Formato | |
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