fIRTree: An Item Response Theory modeling of fuzzy rating data
Applications
2021-12-10 v1
Abstract
In this contribution we describe a novel procedure to represent fuzziness 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 answer 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.
Keywords
Cite
@article{arxiv.2102.02025,
title = {fIRTree: An Item Response Theory modeling of fuzzy rating data},
author = {Antonio Calcagnì},
journal= {arXiv preprint arXiv:2102.02025},
year = {2021}
}