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Decreasing Respondent Heterogeneity by Likert Scales Adjustment via Multipoles

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Stats 2018, 1(1), 169-175; https://doi.org/10.3390/stats1010012
Received: 31 August 2018 / Revised: 4 November 2018 / Accepted: 10 November 2018 / Published: 14 November 2018
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Abstract

A description of Likert scales can be given using the multipoles technique known in quantum physics and applied to behavioral sciences data. This paper considers decomposition of Likert scales by the multipoles for the application of decreasing the respondents’ heterogeneity. Due to cultural and language differences, different respondents habitually use the lower end, the mid-scale, or the upper end of the Likert scales which can lead to distortion and inconsistency in data across respondents. A big impact of different kinds of respondent is well known, for instance, in international studies, and it is called the problem of high and low raters. Application of a multipoles technique to the row-data smoothing via prediction of individual rates by the histogram of the Likert scale tiers produces better results than standard row-centering in data. A numerical example by marketing research data shows that the results are encouraging: while a standard row-centering produces a poor outcome, the dipole-adjustment noticeably improves the obtained segmentation results. View Full-Text
Keywords: Likert scale; high and low raters; respondents heterogeneity; quantum multipoles; marketing research Likert scale; high and low raters; respondents heterogeneity; quantum multipoles; marketing research
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Lipovetsky, S.; Conklin, M. Decreasing Respondent Heterogeneity by Likert Scales Adjustment via Multipoles. Stats 2018, 1, 169-175.

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