Biclustering Models for Two-Mode Ordinal Data

E. Matechou, I. Liu, D. Fernandez, Miguel Farias, B. Gjelsvik

    Research output: Contribution to journalArticlepeer-review

    6 Citations (Scopus)
    43 Downloads (Pure)

    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
    Original languageEnglish
    Pages (from-to)611-624
    JournalPsychometrika
    Volume81
    Issue number3
    Early online date21 Jun 2016
    DOIs
    Publication statusPublished - 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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