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Measuring associations and evaluating forecasts of categorical variables

Author

Listed:
  • Andrei Sirchenko

    (Nyenrode Business University)

  • Jochem Huismans

    (University of Amsterdam)

  • Jan Willem Nijenhuis

    (Nedap NV)

Abstract

This presentation introduces a new Stata command, classify, that computes various measures of association and correlation between two categorical variables (binary, ordinal, or nominal), evaluates the performance of categorical deterministic forecasts, and provides diagnostic probability scores of the accuracy of probabilistic forecasts. We compiled a comprehensive catalogue of 9 diagnostic scores for probabilistic forecasts and over 210 measures of association and correlation employed in different fields, along with the terminological synonymy and bibliography associated with them. In addition to the overall measures, the command computes the category-specific metrics for each observed category and its macro and weighted averages. We also classify all measures according to the two types of symmetry as well as propose and compute the complement and transpose symmetric variants of those measures that are not symmetric.

Suggested Citation

  • Andrei Sirchenko & Jochem Huismans & Jan Willem Nijenhuis, 2023. "Measuring associations and evaluating forecasts of categorical variables," 2023 Stata Conference 19, Stata Users Group.
    • Handle: RePEc:boc:usug23:19
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    File URL: http://repec.org/usug2023/US23_Sirchenko.pdf
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