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Mixed-Effects Location Scale Models for Joint Modeling School Value-Added Effects on the Mean and Variance of Student Achievement

Author

Listed:
  • George Leckie
  • Richard Parker
  • Harvey Goldstein
  • Kate Tilling

    (University of Bristol)

Abstract

School value-added models are widely applied to study, monitor, and hold schools to account for school differences in student learning. The traditional model is a mixed-effects linear regression of student current achievement on student prior achievement, background characteristics, and a school random intercept effect. The latter is referred to as the school value-added score and measures the mean student covariate-adjusted achievement in each school. In this article, we argue that further insights may be gained by additionally studying the variance in this quantity in each school. These include the ability to identify both individual schools and school types that exhibit unusually high or low variability in student achievement, even after accounting for differences in student intakes. We explore and illustrate how this can be done via fitting mixed-effects location scale versions of the traditional school value-added model. We discuss the implications of our work for research and school accountability systems.

Suggested Citation

  • George Leckie & Richard Parker & Harvey Goldstein & Kate Tilling, 2024. "Mixed-Effects Location Scale Models for Joint Modeling School Value-Added Effects on the Mean and Variance of Student Achievement," Journal of Educational and Behavioral Statistics, , vol. 49(6), pages 879-911, December.
    • Handle: RePEc:sae:jedbes:v:49:y:2024:i:6:p:879-911
    DOI: 10.3102/10769986231210808
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    References listed on IDEAS

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    1. Donald Hedeker & Robin J. Mermelstein & Hakan Demirtas, 2008. "An Application of a Mixed-Effects Location Scale Model for Analysis of Ecological Momentary Assessment (EMA) Data," Biometrics, The International Biometric Society, vol. 64(2), pages 627-634, June.
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    4. Lucy Prior & John Jerrim & Dave Thomson & George Leckie, 2021. "A review and evaluation of secondary school accountability in England: Statistical strengths, weaknesses, and challenges for ‘Progress 8’ raised by COVID-19," DoQSS Working Papers 21-12, Quantitative Social Science - UCL Social Research Institute, University College London.
    5. Lucy Prior & John Jerrim & Dave Thomson & George Leckie, 2021. "A review and evaluation of secondary school accountability in England: Statistical strengths, weaknesses, and challenges for 'Progress 8' raised by COVID-19," CEPEO Working Paper Series 21-04, UCL Centre for Education Policy and Equalising Opportunities, revised Apr 2021.
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    7. George Leckie & Harvey Goldstein, 2009. "The limitations of using school league tables to inform school choice," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(4), pages 835-851, October.
    8. George Leckie & Harvey Goldstein, 2015. "A multilevel modelling approach to measuring changing patterns of ethnic composition and segregation among London secondary schools, 2001–2010," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(2), pages 405-424, February.
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    Cited by:

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    2. Den Teuling, Niek G.P. & Ungolo, Francesco & Pauws, Steffen C. & van den Heuvel, Edwin R., 2025. "Latent-class trajectory modeling with a heterogeneous mean-variance relation," Computational Statistics & Data Analysis, Elsevier, vol. 210(C).

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