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An entropy approach to the scaling of ordinal categorical data (1989)

Jefferson, T. R. ; May, J. H. ; Ravi, N.

Springer

Psychometrika 54 (1989), S. 203-215

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ISSN: 1860-0980

Keywords: ordinal categorical data ; entropy ; minimum discrimination information ; scaling ; convex programming

Source: Springer Online Journal Archives 1860-2000

Topics: Psychology

Notes: Abstract This paper studies the problem of scaling ordinal categorical data observed over two or more sets of categories measuring a single characteristic. Scaling is obtained by solving a constrained entropy model which finds the most probable values of the scales given the data. A Kullback-Leibler statistic is generated which operationalizes a measure for the strength of consistency among the sets of categories. A variety of data of two and three sets of categories are analyzed using the entropy approach.

Type of Medium: Electronic Resource

URL: http://dx.doi.org/10.1007/BF02294515

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