Abstract
The work in this paper introduces finite mixture models that can be used tosimultaneously cluster the rows and columns of ordinal categorical responsedata. Model-fitting is performed using the EM algorithm and a fuzzy allocationof rows and columns to corresponding clusters is obtained. The clusteringability of the models is evaluated, and compared to that of k-means,in a simulation study, and demonstrated using two real data sets.
The final publication is available at Springer via http://dx.doi.org/10.1007/s11336-016-9503-3
The final publication is available at Springer via http://dx.doi.org/10.1007/s11336-016-9503-3
Original language | English |
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Pages (from-to) | 611-624 |
Journal | Psychometrika |
Volume | 81 |
Issue number | 3 |
Early online date | 21 Jun 2016 |
DOIs | |
Publication status | Published - Sep 2016 |
Bibliographical note
Article in press, full citation details will be uploaded when available.This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Keywords
- EM algorithm
- fuzzy clustering
- Likert scale
- proportional odds
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Miguel Farias
- Centre for Trust, Peace and Social Relations - Associate Professor Academic
Person: Teaching and Research