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Measuring associations and evaluating forecasts of categorical and discrete variables

Author

Listed:
  • Maik Hamjediers

    (Humboldt Universität zu Berlin)

  • Maximilian Sprengholz

    (Humboldt Universität zu Berlin, Institut für Sozialwissenschaften)

Abstract

This presentation introduces a new Stata command, classify, that constructs a classification table and computes various measures of association between two categorical variables, as well as diagnostic scores of the accuracy of probabilistic and deterministic forecasts of a categorical (binary and multiclass ordinal or nominal) variable. We compiled a comprehensive list of about 200 coefficients, along with the synonymy and bibliography associated with them. In addition to the general measures, the command also computes the class-specific measures for each class as well as their macro and weighted averages.

Suggested Citation

  • Maik Hamjediers & Maximilian Sprengholz, 2023. "Measuring associations and evaluating forecasts of categorical and discrete variables," German Stata Conference 2023 06, Stata Users Group.
    • Handle: RePEc:boc:dsug23:06
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    References listed on IDEAS

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    4. Iacus, Stefano M. & King, Gary & Porro, Giuseppe, 2012. "Causal Inference without Balance Checking: Coarsened Exact Matching," Political Analysis, Cambridge University Press, vol. 20(1), pages 1-24, January.
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