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Robustness Measurement of Comprehensive Evaluation Model Based on the Intraclass Correlation Coefficient

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  • Shilai Xian

    (Department of Mathematic and Statistics, Yunnan University, Kunming 650000, China)

  • Li Zhang

    (Department of Mathematic and Statistics, Yunnan University, Kunming 650000, China)

Abstract

This study proposes a standardized robustness measurement framework for comprehensive evaluation models based on the Intraclass Correlation Coefficient (ICC(3,1)), The framework aims to address two key issues: (1) the non-unique evaluation results caused by the abundance of such models, and (2) the lack of standardization and the arbitrariness in existing robustness testing procedures. Theoretical derivation and simulation confirm that ICC(3,1) exhibits a positive correlation with Kendall’s Coefficient of Concordance (Kendall’s W) and a negative correlation with Root Mean Square Error (RMSE) and Normalized Inversion Index (NII), demonstrating superior stability, discrimination, and interpretability. Under increased noise levels, ICC(3,1) maintains a balance between robustness and sensitivity, supporting its application in robustness evaluation and method selection.

Suggested Citation

  • Shilai Xian & Li Zhang, 2025. "Robustness Measurement of Comprehensive Evaluation Model Based on the Intraclass Correlation Coefficient," Mathematics, MDPI, vol. 13(11), pages 1-20, May.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:11:p:1748-:d:1663945
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    References listed on IDEAS

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    1. Paolo Paruolo & Michaela Saisana & Andrea Saltelli, 2013. "Ratings and rankings: voodoo or science?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(3), pages 609-634, June.
    2. James Foster & Mark McGillivray & Suman Seth, 2012. "Rank Robustness of Composite Indices: Dominance and Ambiguity," OPHI Working Papers 26b, Queen Elizabeth House, University of Oxford.
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