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The Persistence of School-Level Value-Added

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  • Derek C. Briggs
  • Jonathan P. Weeks

Abstract

Using longitudinal data for an entire state from 2004 to 2008, this article describes the results from an empirical investigation of the persistence of value-added school effects on student achievement in reading and math. It shows that when schools are the principal units of analysis rather than teachers, the persistence of estimated school effects across grades can only be reasonably identified by placing strong constraints on the variable persistence model implemented by Lockwood, McCaffrey, Mariano, and Setodji. In general, there are relatively strong correlations between the school effects estimated using these constrained models and a reference model that assumes full persistence. These correlations vary somewhat by grade and the underlying test subject. The results from this study indicate cautious support for previous findings that the assumption of full persistence for cumulative value-added effects may be untenable, and evidence is also presented, which indicates a strong interaction by test subject. However, the practical impact of violating the assumption of full persistence appears to be smaller in the context of schools than it is for teachers.

Suggested Citation

  • Derek C. Briggs & Jonathan P. Weeks, 2011. "The Persistence of School-Level Value-Added," Journal of Educational and Behavioral Statistics, , vol. 36(5), pages 616-637, October.
    • Handle: RePEc:sae:jedbes:v:36:y:2011:i:5:p:616-637
    DOI: 10.3102/1076998610396887
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    References listed on IDEAS

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    1. Derek C. Briggs & Jonathan P. Weeks, 2009. "The Sensitivity of Value-Added Modeling to the Creation of a Vertical Score Scale," Education Finance and Policy, MIT Press, vol. 4(4), pages 384-414, October.
    2. Douglas N. Harris, 2009. "Would Accountability Based on Teacher Value Added Be Smart Policy? An Examination of the Statistical Properties and Policy Alternatives," Education Finance and Policy, MIT Press, vol. 4(4), pages 319-350, October.
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    Citations

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    Cited by:

    1. Karl, Andrew T. & Yang, Yan & Lohr, Sharon L., 2013. "Efficient maximum likelihood estimation of multiple membership linear mixed models, with an application to educational value-added assessments," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 13-27.
    2. Jorge Manzi & Ernesto San Martín & Sébastien Van Bellegem, 2014. "School System Evaluation by Value Added Analysis Under Endogeneity," Psychometrika, Springer;The Psychometric Society, vol. 79(1), pages 130-153, January.
    3. Page, Garritt L. & San Martin, Ernesto & Torres Irribarra, David & Van Bellegem, Sébastien, 2024. "Temporally Dynamic, Cohort-Varying Value-Added Models," LIDAM Discussion Papers CORE 2024009, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Heikki Pursiainen & Mika Kortelainen & Jenni Pääkkönen, 2014. "Impact of School Quality on Educational Attainment - Evidence from Finnish High Schools," ERSA conference papers ersa14p711, European Regional Science Association.
    5. Susanna Loeb & Michael S. Christian & Heather Hough & Robert H. Meyer & Andrew B. Rice & Martin R. West, 2019. "School Differences in Social–Emotional Learning Gains: Findings From the First Large-Scale Panel Survey of Students," Journal of Educational and Behavioral Statistics, , vol. 44(5), pages 507-542, October.

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