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An Explained Variation Measure for Ordinal Response Models With Comparisons to Other Ordinal R² Measures

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  • Michael G. Lacy

    (Colorado State University)

Abstract

No explained variation (R 2 ) measure for ordinal response models enjoys wide use, and such measures have in fact received little specific attention or evaluation. To remedy this gap, the author presents and justifies R 2 O , an explained variation measure for ordinal response models, which is based on a recent ordinal dispersion measure. The use and function of R 2 O is illustrated, and the performance of it and other ordinal R 2 measures is compared via a series of simulated sampling and variable selection experiments. The R 2 O and a bias-adjusted version of it perform well in the simulation experiments and have a number of other advantages that make them attractive as measures of fit for any ordinal response model.

Suggested Citation

  • Michael G. Lacy, 2006. "An Explained Variation Measure for Ordinal Response Models With Comparisons to Other Ordinal R² Measures," Sociological Methods & Research, , vol. 34(4), pages 469-520, May.
    • Handle: RePEc:sae:somere:v:34:y:2006:i:4:p:469-520
    DOI: 10.1177/0049124106286329
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    Cited by:

    1. Selen Cakmakyapan & Haydar Demirhan, 2017. "A Monte Carlo-based pseudo-coefficient of determination for generalized linear models with binary outcome," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(14), pages 2458-2482, October.
    2. Maurizio Bovi, 2016. "The tale of two expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(6), pages 2677-2705, November.

    More about this item

    Keywords

    ordinal response models; variation measure; R2O; R2 measures;
    All these keywords.

    JEL classification:

    • R2 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis

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