Biclustering Models for Two-Mode Ordinal Data

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

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    6 Citations (Scopus)
    27 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

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    Keywords

    • EM algorithm
    • fuzzy clustering
    • Likert scale
    • proportional odds

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  • Cite this

    Matechou, E., Liu, I., Fernandez, D., Farias, M., & Gjelsvik, B. (2016). Biclustering Models for Two-Mode Ordinal Data. Psychometrika, 81(3), 611-624. https://doi.org/10.1007/s11336-016-9503-3