The information-theoretic measures of consensus, dissent and agreement are used to address the problem of the assignment of weights in recognition of expert opinions, and interval weights to reflect categorical weights. All measures are bounded in the 0 to 1 interval. Dissent is also interpreted as an indicator of dispersion. Thus, the values selected by a panel of experts is calculated for each targeted category and the category with the highest resulting value is the one chosen to represent the overall expert judgment. Further, the distances between threat levels can be calculated and the dispersion for the distribution may also be calculated. This is different from the standard statistical measures of variance for categorical values are based on an ordinal scale of ordered categories and the standard deviation requires the presence of an interval or ratio scale. Illustrations are shown to describe the functionality of the measures.
[1]
M. J. Wierman,et al.
Placing the Dissonance Measure in the Context of Generalized Information Theory
,
2006,
NAFIPS 2006 - 2006 Annual Meeting of the North American Fuzzy Information Processing Society.
[2]
Mark J. Wierman,et al.
Consensus and dissention: A measure of ordinal dispersion
,
2007,
Int. J. Approx. Reason..
[3]
M. J. Wierman,et al.
An information theoretic measure for the evaluation of ordinal scale data
,
2006,
Behavior research methods.
[4]
W.J. Tastle,et al.
Consensus and dissention: a new measure of agreement
,
2005,
NAFIPS 2005 - 2005 Annual Meeting of the North American Fuzzy Information Processing Society.