 Modeling uncertainty with the truncated zeta distribution in mixture models for ordinal responsesDayang Dai and Dabuxilatu Wang Communications in Statistics - Theory and Methods, 2025, vol. 54, issue 13, 3976-4000 Abstract: In recent three decades, there has been a rapid increasing interest in the mixture models for ordinal responses, and the classical CUB model as a fundamental one has been extended to different preference and uncertainty models. In this article, based on a response style supported by Zipf’s law, we propose a novel mixture model for ordinal responses via replacing the uncertainty component of the CUB model with a truncated Zeta distribution. Parameters estimation with EM algorithm, inferential issues with respect to the approximation of a truncated Riemann Zeta function and estimators’ variance-covariance information matrix are investigated. The advantages of the proposed model over the CUB model have been illustrated with simulations of two sets of Monte Carlo experiments and practical applications of a health survey and a bicycle use. The intention of the article is to distinguish the respondents’ true preference from the response style of “the higher, the less”, so as to understand more reasonably the formation causes of ordinal responses. Date: 2025 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:54:y:2025:i:13:p:3976-4000 Ordering information: This journal article can be ordered from DOI: 10.1080/03610926.2024.2409373 Access Statistics for this article Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals |
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