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Meta‐analysis using multilevel models with an application to the study of class size effects

Author

Listed:
  • Harvey Goldstein
  • Min Yang
  • Rumana Omar
  • Rebecca Turner
  • Simon Thompson

Abstract

Meta‐analysis is formulated as a special case of a multilevel (hierarchical data) model in which the highest level is that of the study and the lowest level that of an observation on an individual respondent. Studies can be combined within a single model where the responses occur at different levels of the data hierarchy and efficient estimates are obtained. An example is given from studies of class sizes and achievement in schools, where study data are available at the aggregate level in terms of overall mean values for classes of different sizes, and also at the student level.

Suggested Citation

  • Harvey Goldstein & Min Yang & Rumana Omar & Rebecca Turner & Simon Thompson, 2000. "Meta‐analysis using multilevel models with an application to the study of class size effects," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 49(3), pages 399-412.
    • Handle: RePEc:bla:jorssc:v:49:y:2000:i:3:p:399-412
    DOI: 10.1111/1467-9876.00200
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    Cited by:

    1. Yongyun Shin & Stephen W. Raudenbush, 2011. "The Causal Effect of Class Size on Academic Achievement," Journal of Educational and Behavioral Statistics, , vol. 36(2), pages 154-185, April.
    2. George Leckie, 2022. "A celebration of Harvey Goldstein’s lifetime contributions: Memories of working with Harvey Goldstein on educational research and statistics," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 758-762, July.
    3. Ugur, Mehmet & Dasgupta, Nandini, 2011. "Corruption and economic growth: A meta-analysis of the evidence on low-income countries and beyond," MPRA Paper 31226, University Library of Munich, Germany, revised 31 May 2011.
    4. Michael Sobel & David Madigan & Wei Wang, 2017. "Causal Inference for Meta-Analysis and Multi-Level Data Structures, with Application to Randomized Studies of Vioxx," Psychometrika, Springer;The Psychometric Society, vol. 82(2), pages 459-474, June.
    5. Laura De Dominicis & Raymond J. G. M. Florax & Henri L. F. De Groot, 2008. "A Meta‐Analysis On The Relationship Between Income Inequality And Economic Growth," Scottish Journal of Political Economy, Scottish Economic Society, vol. 55(5), pages 654-682, November.
    6. Maria Dolores Montoya Diaz, 2007. "Efetividade no Ensino Superior Brasileiro:Aplicação de Modelos Multinível À Análise dos Resultados do Exame Nacional de Cursos," Economia, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 8(1), pages 93-120.
    7. William J. Browne, 2022. "A celebration of Harvey Goldstein’s lifetime contributions: Memories of working with Harvey Goldstein on multilevel modelling methods and applications," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 753-758, July.
    8. K. Kounetas & G. Androulakis & M. Kaisari & G. Manousakis, 2023. "Educational reforms and secondary school's efficiency performance in Greece: a bootstrap DEA and multilevel approach," Operational Research, Springer, vol. 23(1), pages 1-29, March.
    9. Simone Santoni & Paolo Ferri & Maria Lusiani, 2013. "Novelty Conduits and Forms of Network Ties: To Bond or to Bridge?," Working Papers 34, Department of Management, Università Ca' Foscari Venezia.

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