Skip to main content

Biclustering models for two-mode ordinal data

Matechou, Eleni, Liu, Ivy, Fernandez, Daniel, Farias, Miguel, Gjelsvik, Bergljot (2016) Biclustering models for two-mode ordinal data. Psychometrika, . ISSN 0033-3123. E-ISSN 1860-0980. (doi:10.1007/s11336-016-9503-3) (KAR id:48948)

PDF Publisher pdf
Language: English
Click to download this file (518kB) Preview
[thumbnail of art%3A10.1007%2Fs11336-016-9503.pdf]
Preview
This file may not be suitable for users of assistive technology.
Request an accessible format
Official URL:
http://link.springer.com/article/10.1007/s11336-01...

Abstract

The work in this paper introduces finite mixture models that can be used to simul-

taneously cluster the rows and columns of two-mode ordinal categorical response data,

such as those resulting from Likert scale responses. We use the popular proportional

odds parameterisation and propose models which provide insights into major patterns

in the data. Model-fitting is performed using the EM algorithm and a fuzzy allocation

of rows and columns to corresponding clusters is obtained. The clustering ability of the

models is evaluated in a simulation study and demonstrated using two real data sets.

Item Type: Article
DOI/Identification number: 10.1007/s11336-016-9503-3
Uncontrolled keywords: EM algorithm; fuzzy clustering; Likert scale; proportional odds; SEAK
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Eleni Matechou
Date Deposited: 08 Jun 2015 09:11 UTC
Last Modified: 16 Feb 2021 13:25 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/48948 (The current URI for this page, for reference purposes)
Matechou, Eleni: https://orcid.org/0000-0003-3626-844X
  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.