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The impact of sampling variation on peer measures: a comment on a proposal to adjust estimates for measurement error

  • Pedro N. Silva

    ()

    (Instituto Brasileiro de Geografia e Estatística, Rio de Janeiro)

  • John Micklewright

    ()

    (Department of Quantitative Social Science, Institute of Education, University of London)

  • Sylke V. Schnepf

    ()

    (Southampton Statistical Sciences Research Institute and School of Social Sciences, University of Southampton)

Investigation of peer effects on pupil’s achievement with survey data on samples of schools and pupils within schools may mean that only a random sample of peers is observed for each individual pupil. This generates classical measurement error on peer variables. Hence under OLS model fitting the estimated peer group effects in a regression model are biased towards zero (attenuation). A simple adjustment for this kind of measurement error was proposed by Neidell and Waldfogel (2008). We review the derivation of the simple adjustment and suggest that it is not properly justified.

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Paper provided by Department of Quantitative Social Science - UCL Institute of Education, University College London in its series DoQSS Working Papers with number 12-12.

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Date of creation: 20 Dec 2012
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Handle: RePEc:qss:dqsswp:1212
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  1. Ammermüller, Andreas & Pischke, Jörn-Steffen, 2006. "Peer Effects in European Primary Schools: Evidence from PIRLS," IZA Discussion Papers 2077, Institute for the Study of Labor (IZA).
  2. Matthew Neidell & Jane Waldfogel, 2008. "Cognitive and Non-Cognitive Peer Effects in Early Education," NBER Working Papers 14277, National Bureau of Economic Research, Inc.
  3. Andreas Ammermueller & Jörn-Steffen Pischke, 2009. "Peer Effects in European Primary Schools: Evidence from the Progress in International Reading Literacy Study," Journal of Labor Economics, University of Chicago Press, vol. 27(3), pages 315-348, 07.
  4. Micklewright, John & Schnepf, Sylke V. & Silva, Pedro N., 2012. "Peer effects and measurement error: The impact of sampling variation in school survey data (evidence from PISA)," Economics of Education Review, Elsevier, vol. 31(6), pages 1136-1142.
  5. Øystein Kravdal, 2006. "A simulation-based assessment of the bias produced when using averages from small DHS clusters as contextual variables in multilevel models," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 15(1), pages 1-20, July.
  6. Matthew Neidell & Jane Waldfogel, 2010. "Cognitive and Noncognitive Peer Effects in Early Education," The Review of Economics and Statistics, MIT Press, vol. 92(3), pages 562-576, August.
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