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Journal article

The knowledge content of statistical data

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  • Preuss, Lucien Feldeggstrasse 74, Ch 8008, Zürich, Switzerland
  • Vorkauf, Helmut University of Fribourg and Swiss Federal Office of Public Health, Switzerland
    1997
Published in:
  • Psychometrika. - Springer-Verlag. - 1997, vol. 62, no. 1, p. 133-161
English An information-theoretic framework is used to analyze the knowledge content in multivariate cross classified data. Several related measures based directly on the information concept are proposed: the knowledge content (S) of a cross classification, its terseness (Zeta), and the separability (Gamma X ) of one variable, given all others. Exemplary applications are presented which illustrate the solutions obtained where classical analysis is unsatisfactory, such as optimal grouping, the analysis of very skew tables, or the interpretation of well-known paradoxes. Further, the separability suggests a solution for the classic problem of inductive inference which is independent of sample size
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Language
  • English
Classification
Medicine
License
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The Psychometric Society, 1997
Identifiers
  • RERO DOC 313051
  • SWISSBIB (NATIONALLICENCE)springer-10.1007/BF02294784
  • DOI 10.1007/BF02294784
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https://sonar.ch/global/documents/306814
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