Biclustering Models for Two-Mode Ordinal Data

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

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    8 Citations (Scopus)
    67 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 - Sept 2016

    Bibliographical note

    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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