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Adequateness and interpretability of objective functions in ordinal data analysis

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  • Herden, Gerhard
  • Pallack, Andreas

Abstract

Objective functions that are applied in ordinal data analysis must be adequate, i.e. carefully adapted to the structure of the observed data. In addition, any analysis of data that is based upon objective functions must lead to interpretable results. After a general characterization of adequate objective functions in ordinal data analysis, therefore, the particular problems of constructing adequate and interpretable dissimilarity coefficients and correlation coefficients in ordinal data analysis, stress measures (stress functions) in non-metric scaling and generalized stress measures or correlation coefficients in any theory of rank estimation will be discussed.

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  • Herden, Gerhard & Pallack, Andreas, 2005. "Adequateness and interpretability of objective functions in ordinal data analysis," Journal of Multivariate Analysis, Elsevier, vol. 94(1), pages 19-69, May.
  • Handle: RePEc:eee:jmvana:v:94:y:2005:i:1:p:19-69
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    1. Yoshio Takane & Forrest Young & Jan Leeuw, 1977. "Nonmetric individual differences multidimensional scaling: An alternating least squares method with optimal scaling features," Psychometrika, Springer;The Psychometric Society, vol. 42(1), pages 7-67, March.
    2. Richard Johnson, 1975. "A simple method for pairwise monotone regression," Psychometrika, Springer;The Psychometric Society, vol. 40(2), pages 163-168, June.
    3. Michael W. Trosset, 2002. "Extensions of Classical Multidimensional Scaling via Variable Reduction," Computational Statistics, Springer, vol. 17(2), pages 147-163, July.
    4. Norman Cliff, 1989. "Ordinal consistency and ordinal true scores," Psychometrika, Springer;The Psychometric Society, vol. 54(1), pages 75-91, March.
    5. S. Winsberg & J. Ramsay, 1983. "Monotone spline transformations for dimension reduction," Psychometrika, Springer;The Psychometric Society, vol. 48(4), pages 575-595, December.
    6. Jan Leeuw, 1977. "Correctness of Kruskal's algorithms for monotone regression with ties," Psychometrika, Springer;The Psychometric Society, vol. 42(1), pages 141-144, March.
    7. Robert Schulman, 1976. "Correlation and prediction in ordinal test theory," Psychometrika, Springer;The Psychometric Society, vol. 41(3), pages 329-340, September.
    8. Herden, G., 1990. "Dissimilarity coefficients which are independent of a special set of data," Mathematical Social Sciences, Elsevier, vol. 20(1), pages 73-90, August.
    9. Berrie Zielman & Willem Heiser, 1993. "Analysis of asymmetry by a slide-vector," Psychometrika, Springer;The Psychometric Society, vol. 58(1), pages 101-114, March.
    10. Herden, G., 1993. "Some aspects of qualitative data analysis," Mathematical Social Sciences, Elsevier, vol. 26(2), pages 105-138, September.
    11. Mathar, Rudolf, 1990. "Multidimensional scaling with constraints on the configuration," Journal of Multivariate Analysis, Elsevier, vol. 33(2), pages 151-156, May.
    12. Norman Cliff, 1979. "Test theory without true scores?," Psychometrika, Springer;The Psychometric Society, vol. 44(4), pages 373-393, December.
    13. J. Carroll & Suzanne Winsberg, 1995. "Fitting an extended INDSCAL model to three-way proximity data," Journal of Classification, Springer;The Classification Society, vol. 12(1), pages 57-71, March.
    14. Suzanne Winsberg & J. Douglas Carroll, 1989. "A quasi-nonmetric method for multidimensional scaling VIA an extended euclidean model," Psychometrika, Springer;The Psychometric Society, vol. 54(2), pages 217-229, June.
    15. J. Kruskal, 1964. "Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis," Psychometrika, Springer;The Psychometric Society, vol. 29(1), pages 1-27, March.
    16. Herden, Gerhard & Pallack, Andreas, 2002. "Consistency in ordinal data analysis I," Mathematical Social Sciences, Elsevier, vol. 43(1), pages 79-113, January.
    17. Robert Schulman, 1978. "Individual distributions under ordinal measurement," Psychometrika, Springer;The Psychometric Society, vol. 43(1), pages 19-29, March.
    18. W. Schucany & W. Frawley, 1973. "A rank test for two group concordance," Psychometrika, Springer;The Psychometric Society, vol. 38(2), pages 249-258, June.
    19. Louis Guttman, 1968. "A general nonmetric technique for finding the smallest coordinate space for a configuration of points," Psychometrika, Springer;The Psychometric Society, vol. 33(4), pages 469-506, December.
    20. Norman Cliff, 1977. "A theory of consistency of ordering generalizable to tailored testing," Psychometrika, Springer;The Psychometric Society, vol. 42(3), pages 375-399, September.
    21. Norman Cliff & John Donoghue, 1992. "Ordinal test fidelity estimated by an item sampling model," Psychometrika, Springer;The Psychometric Society, vol. 57(2), pages 217-236, June.
    22. Warren Torgerson, 1952. "Multidimensional scaling: I. Theory and method," Psychometrika, Springer;The Psychometric Society, vol. 17(4), pages 401-419, December.
    23. Robert schulman & Richard Haden, 1975. "A test theory model for ordinal measurements," Psychometrika, Springer;The Psychometric Society, vol. 40(4), pages 455-472, December.
    24. J. Ramsay, 1977. "Monotonic weighted power transformations to additivity," Psychometrika, Springer;The Psychometric Society, vol. 42(1), pages 83-109, March.
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