An information theoretic measure for the evaluation of ordinal scale data

W. J. Tastle, M. J. Wierman

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

This article describes a new measure of dispersion as an indication of consensus and dissention. Building on the generally accepted Shannon entropy, this measure utilizes a probability distribution and the ordered ranking of categories in an ordinal scale distribution to yield a value confined to the unit interval. Unlike other measures that need to be normalized, this measure is always in the interval 0 to 1. The measure is typically applied to the Likert scale to determine degrees of agreement among ordinal-ranked categories when one is dealing with data collection and analysis, although other scales are possible. Using this measure, investigators can easily determine the proximity of ordinal data to consensus (agreement) or dissention. Consensus and dissention are defined relative to the degree of proximity of values constituting a frequency distribution on the ordinal scale measure. The authors identify a set of criteria that a measure must satisfy in order to be an acceptable indicator of consensus and show how the consensus measure satisfies all the criteria.

Original languageEnglish
Pages (from-to)487-494
Number of pages8
JournalBehavior Research Methods
Volume38
Issue number3
StatePublished - Aug 2006

Fingerprint

Entropy
Research Personnel

All Science Journal Classification (ASJC) codes

  • Psychology(all)
  • Psychology (miscellaneous)
  • Experimental and Cognitive Psychology

Cite this

An information theoretic measure for the evaluation of ordinal scale data. / Tastle, W. J.; Wierman, M. J.

In: Behavior Research Methods, Vol. 38, No. 3, 08.2006, p. 487-494.

Research output: Contribution to journalArticle

Tastle, W. J. ; Wierman, M. J. / An information theoretic measure for the evaluation of ordinal scale data. In: Behavior Research Methods. 2006 ; Vol. 38, No. 3. pp. 487-494.
@article{a5be22ef641041389ef50116e7c94c9b,
title = "An information theoretic measure for the evaluation of ordinal scale data",
abstract = "This article describes a new measure of dispersion as an indication of consensus and dissention. Building on the generally accepted Shannon entropy, this measure utilizes a probability distribution and the ordered ranking of categories in an ordinal scale distribution to yield a value confined to the unit interval. Unlike other measures that need to be normalized, this measure is always in the interval 0 to 1. The measure is typically applied to the Likert scale to determine degrees of agreement among ordinal-ranked categories when one is dealing with data collection and analysis, although other scales are possible. Using this measure, investigators can easily determine the proximity of ordinal data to consensus (agreement) or dissention. Consensus and dissention are defined relative to the degree of proximity of values constituting a frequency distribution on the ordinal scale measure. The authors identify a set of criteria that a measure must satisfy in order to be an acceptable indicator of consensus and show how the consensus measure satisfies all the criteria.",
author = "Tastle, {W. J.} and Wierman, {M. J.}",
year = "2006",
month = "8",
language = "English",
volume = "38",
pages = "487--494",
journal = "Behavior Research Methods",
issn = "1554-351X",
publisher = "Springer New York",
number = "3",

}

TY - JOUR

T1 - An information theoretic measure for the evaluation of ordinal scale data

AU - Tastle, W. J.

AU - Wierman, M. J.

PY - 2006/8

Y1 - 2006/8

N2 - This article describes a new measure of dispersion as an indication of consensus and dissention. Building on the generally accepted Shannon entropy, this measure utilizes a probability distribution and the ordered ranking of categories in an ordinal scale distribution to yield a value confined to the unit interval. Unlike other measures that need to be normalized, this measure is always in the interval 0 to 1. The measure is typically applied to the Likert scale to determine degrees of agreement among ordinal-ranked categories when one is dealing with data collection and analysis, although other scales are possible. Using this measure, investigators can easily determine the proximity of ordinal data to consensus (agreement) or dissention. Consensus and dissention are defined relative to the degree of proximity of values constituting a frequency distribution on the ordinal scale measure. The authors identify a set of criteria that a measure must satisfy in order to be an acceptable indicator of consensus and show how the consensus measure satisfies all the criteria.

AB - This article describes a new measure of dispersion as an indication of consensus and dissention. Building on the generally accepted Shannon entropy, this measure utilizes a probability distribution and the ordered ranking of categories in an ordinal scale distribution to yield a value confined to the unit interval. Unlike other measures that need to be normalized, this measure is always in the interval 0 to 1. The measure is typically applied to the Likert scale to determine degrees of agreement among ordinal-ranked categories when one is dealing with data collection and analysis, although other scales are possible. Using this measure, investigators can easily determine the proximity of ordinal data to consensus (agreement) or dissention. Consensus and dissention are defined relative to the degree of proximity of values constituting a frequency distribution on the ordinal scale measure. The authors identify a set of criteria that a measure must satisfy in order to be an acceptable indicator of consensus and show how the consensus measure satisfies all the criteria.

UR - http://www.scopus.com/inward/record.url?scp=33947496575&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33947496575&partnerID=8YFLogxK

M3 - Article

C2 - 17186759

AN - SCOPUS:33947496575

VL - 38

SP - 487

EP - 494

JO - Behavior Research Methods

JF - Behavior Research Methods

SN - 1554-351X

IS - 3

ER -