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Why use arbitrary points scores?: ordered categories in models of educational progress

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  • A. Fielding

Abstract

Much statistical modelling of random effects on ordered responses, particularly of grades in educational research, continues to use linear models and to treat the responses through arbitrary scores. Methodological and software developments now facilitate the proper treatment of such situations through more realistic generalized random‐effects models. This paper reviews some methodological comparisons of these approaches. It highlights the flexibility offered by the macro facilities of the multilevel random‐effects software MLwiN. It considers applications to an analysis of primary school educational progress from reception to England and Wales national curriculum key stage 1 mathematics. By contrasting the results from generalized modelling and scoring approaches it draws some conclusions about the theoretical, methodological and practical options that are available. It also considers that results of generalized random‐model estimation may be more intelligible to users of analytical results.

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  • A. Fielding, 1999. "Why use arbitrary points scores?: ordered categories in models of educational progress," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(3), pages 303-328.
    • Handle: RePEc:bla:jorssa:v:162:y:1999:i:3:p:303-328
    DOI: 10.1111/1467-985X.00137
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    Cited by:

    1. Kersting, Erasmus & Kilby, Christopher, 2014. "Aid and democracy redux," European Economic Review, Elsevier, vol. 67(C), pages 125-143.
    2. Jacobo Rozo Alzate, 2017. "La educación secundaria y sus dos dimensiones. Efectos del barrio y del colegio sobre los resultados saber 11," Revista de Economía del Rosario, Universidad del Rosario, vol. 20(1), pages 33-69, June.
    3. Brown, Sarah & Taylor, Karl & Wheatley Price, Stephen, 2005. "Debt and distress: Evaluating the psychological cost of credit," Journal of Economic Psychology, Elsevier, vol. 26(5), pages 642-663, October.
    4. Salule Joseph Masangwi & Anthony Martin Grimason & Tracy Dawn Morse & Lawrence Kazembe & Neil Ferguson & George Christopher Jabu, 2012. "Pattern of Maternal Knowledge and Its Implications for Diarrhoea Control in Southern Malawi: Multilevel Thresholds of Change Analysis," IJERPH, MDPI, vol. 9(3), pages 1-15, March.
    5. Michael A. Shields & Stephen Wheatley Price, 2005. "Exploring the economic and social determinants of psychological well‐being and perceived social support in England," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(3), pages 513-537, July.
    6. Corrado, L. & Fingleton, B., 2011. "Multilevel Modelling with Spatial Effects," SIRE Discussion Papers 2011-13, Scottish Institute for Research in Economics (SIRE).
    7. Rutherford, Gillian N. & Bebi, Peter & Edwards, Peter J. & Zimmermann, Niklaus E., 2008. "Assessing land-use statistics to model land cover change in a mountainous landscape in the European Alps," Ecological Modelling, Elsevier, vol. 212(3), pages 460-471.
    8. Antony Fielding, 2004. "Scaling for Residual Variance Components of Ordered Category Responses in Generalised Linear Mixed Multilevel Models," Quality & Quantity: International Journal of Methodology, Springer, vol. 38(4), pages 425-433, August.

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