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R-squared and prediction in regression with ordered quantitative response

Author

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  • Diane Dancer
  • Andrew Tremayne

Abstract

This paper is concerned with the use of regression methods to predict values of a response variable when that variable is naturally ordered. An application to the prediction of student examination performance is provided and it is argued that, although individual scores are unlikely to be well predicted at the extremes of the range using the conditional mean, conditional on covariates, it is possible to usefully predict where an individual is likely to feature in the rank order of performance.

Suggested Citation

  • Diane Dancer & Andrew Tremayne, 2005. "R-squared and prediction in regression with ordered quantitative response," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(5), pages 483-493.
    • Handle: RePEc:taf:japsta:v:32:y:2005:i:5:p:483-493
    DOI: 10.1080/02664760500079423
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    Cited by:

    1. Redson Mankishi & Austin Mwange & Windu Matoka, 2025. "Exploring the Relationship Between Capital Structure and SME Profitability: A Case Study of Lusaka's Electronic Device Market," East African Finance Journal, East African Finance Journal, vol. 4(1).
    2. Sofia Giantsidi & Claudia Tarantola, 2026. "The self-adaptive Cuckoo genetic algorithm for echo state networks optimization," Digital Finance, Springer, vol. 8(1), pages 1-29, March.

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