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Now, whose schools are really better (or weaker) than Germany's? A multiple testing approach

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  • Hanck, Christoph
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    Abstract

    Using PIRLS (Progress in International Reading Literacy Study) data, we investigate which countries' schools can be classified as significantly better or weaker than Germany's as regards the reading literacy of primary school children. The 'standard' approach is to conduct separate tests for each country relative to the reference country (Germany) and to reject the null of equally good schools for all those countries whose p-value satisfies pi [less-than-or-equals, slant] 0.05. We demonstrate that this approach ignores the multiple testing nature of the problem and thus overstates differences between schooling systems by producing unwarranted rejections of the null. We employ various multiple testing techniques to remedy this problem. The results suggest that the 'standard' approach may overstate the number of significantly different countries by up to 30%.

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    Bibliographic Info

    Article provided by Elsevier in its journal Economic Modelling.

    Volume (Year): 28 (2011)
    Issue (Month): 4 (July)
    Pages: 1739-1746

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    Handle: RePEc:eee:ecmode:v:28:y:2011:i:4:p:1739-1746

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    Web page: http://www.elsevier.com/locate/inca/30411

    Related research

    Keywords: PIRLS Multiple testing Multi-country comparisons;

    References

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    1. Eric A. Hanushek & Ludger Wössmann, 2006. "Does Educational Tracking Affect Performance and Inequality? Differences- in-Differences Evidence Across Countries," Economic Journal, Royal Economic Society, vol. 116(510), pages C63-C76, 03.
    2. Romano, Joseph P. & Shaikh, Azeem M. & Wolf, Michael, 2008. "Formalized Data Snooping Based On Generalized Error Rates," Econometric Theory, Cambridge University Press, vol. 24(02), pages 404-447, April.
    3. Spanos, Aris, 2010. "Statistical adequacy and the trustworthiness of empirical evidence: Statistical vs. substantive information," Economic Modelling, Elsevier, vol. 27(6), pages 1436-1452, November.
    4. Wo[ss]mann, Ludger & West, Martin, 2006. "Class-size effects in school systems around the world: Evidence from between-grade variation in TIMSS," European Economic Review, Elsevier, vol. 50(3), pages 695-736, April.
    5. Deckers, Thomas & Hanck, Christoph, 2009. "Multiple Testing Techniques in Growth Econometrics," MPRA Paper 17843, University Library of Munich, Germany.
    6. Hendrik Jürges & Kerstin Schneider, 2007. "Fair ranking of teachers," Empirical Economics, Springer, vol. 32(2), pages 411-431, May.
    7. Woo, Jaejoon, 2003. "Economic, political, and institutional determinants of public deficits," Journal of Public Economics, Elsevier, vol. 87(3-4), pages 387-426, March.
    8. Joseph P. Romano & Michael Wolf, 2003. "Stepwise multiple testing as formalized data snooping," Economics Working Papers 712, Department of Economics and Business, Universitat Pompeu Fabra.
    9. Yoav Benjamini & Abba M. Krieger & Daniel Yekutieli, 2006. "Adaptive linear step-up procedures that control the false discovery rate," Biometrika, Biometrika Trust, vol. 93(3), pages 491-507, September.
    10. Savin, N.E., 1984. "Multiple hypothesis testing," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 14, pages 827-879 Elsevier.
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