IDEAS home Printed from https://ideas.repec.org/a/bla/jorssa/v172y2009i4p835-851.html
   My bibliography  Save this article

The limitations of using school league tables to inform school choice

Author

Listed:
  • George Leckie
  • Harvey Goldstein

Abstract

Summary. In England, so‐called ‘league tables’ based on examination results and test scores are published annually, ostensibly to inform parental choice of secondary schools. A crucial limitation of these tables is that the most recent published information is based on the current performance of a cohort of pupils who entered secondary schools several years earlier, whereas for choosing a school it is the future performance of the current cohort that is of interest. We show that there is substantial uncertainty in predicting such future performance and that incorporating this uncertainty leads to a situation where only a handful of schools’ future performances can be separated from both the overall mean and from one another with an acceptable degree of precision. This suggests that school league tables, including value‐added tables, have very little to offer as guides to school choice.

Suggested Citation

  • 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.
  • Handle: RePEc:bla:jorssa:v:172:y:2009:i:4:p:835-851
    DOI: 10.1111/j.1467-985X.2009.00597.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-985X.2009.00597.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1467-985X.2009.00597.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. David Afshartous & Michael Wolf, 2007. "Avoiding ‘data snooping’ in multilevel and mixed effects models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(4), pages 1035-1059, October.
    2. Harvey Goldstein & Michael J. R. Healy, 1995. "The Graphical Presentation of a Collection of Means," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 158(1), pages 175-177, January.
    3. Sheila M. Bird & Cox Sir David & Vern T. Farewell & Goldstein Harvey & Holt Tim & Smith Peter C., 2005. "Performance indicators: good, bad, and ugly," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(1), pages 1-27, January.
    4. Stephen W. Raudenbush & JDouglas Willms, 1995. "The Estimation of School Effects," Journal of Educational and Behavioral Statistics, , vol. 20(4), pages 307-335, December.
    5. Harvey Goldstein & David J. Spiegelhalter, 1996. "League Tables and Their Limitations: Statistical Issues in Comparisons of Institutional Performance," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(3), pages 385-409, May.
    6. Harvey Goldstein & Sally Thomas, 1996. "Using Examination Results as Indicators of School and College Performance," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(1), pages 149-163, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Anders Skrondal & Sophia Rabe‐Hesketh, 2009. "Prediction in multilevel generalized linear models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(3), pages 659-687, June.
    2. Pickery, Jan, 2002. "Contextual effects on the vote in Germany: A multilevel analysis," Discussion Papers, Research Unit: Institutions and Social Change FS III 02-202, WZB Berlin Social Science Center.
    3. Isabella Sulis & Mariano Porcu & Vincenza Capursi, 2019. "On the Use of Student Evaluation of Teaching: A Longitudinal Analysis Combining Measurement Issues and Implications of the Exercise," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(3), pages 1305-1331, April.
    4. Gwyn Bevan & Richard Hamblin, 2009. "Hitting and missing targets by ambulance services for emergency calls: effects of different systems of performance measurement within the UK," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(1), pages 161-190, January.
    5. David I. Ohlssen & Linda D. Sharples & David J. Spiegelhalter, 2007. "A hierarchical modelling framework for identifying unusual performance in health care providers," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(4), pages 865-890, October.
    6. Jill Johnes, 2006. "Measuring Efficiency: A Comparison of Multilevel Modelling and Data Envelopment Analysis in the Context of Higher Education," Bulletin of Economic Research, Wiley Blackwell, vol. 58(2), pages 75-104, April.
    7. Columbu, Silvia & Porcu, Mariano & Sulis, Isabella, 2021. "University choice and the attractiveness of the study area: Insights on the differences amongst degree programmes in Italy based on generalised mixed-effect models," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).
    8. 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.
    9. Paul Hewson & Keming Yu, 2008. "Quantile regression for binary performance indicators," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 401-418, September.
    10. Corak, Miles & Lauzon, Darren, 2009. "Differences in the distribution of high school achievement: The role of class-size and time-in-term," Economics of Education Review, Elsevier, vol. 28(2), pages 189-198, April.
    11. Mutz, Rüdiger & Daniel, Hans-Dieter, 2018. "The bibliometric quotient (BQ), or how to measure a researcher’s performance capacity: A Bayesian Poisson Rasch model," Journal of Informetrics, Elsevier, vol. 12(4), pages 1282-1295.
    12. Magne Mogstad & Joseph P. Romano & Azeem Shaikh & Daniel Wilhelm, 2020. "Inference for Ranks with Applications to Mobility across Neighborhoods and Academic Achievement across Countries," NBER Working Papers 26883, National Bureau of Economic Research, Inc.
    13. Elena Pirani & Daniele Vignoli, 2021. "Childbearing Across Partnerships in Italy: Prevalence, Correlates, Social Gradient," Econometrics Working Papers Archive 2021_15, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    14. Cory Koedel & Jiaxi Li, 2016. "The Efficiency Implications Of Using Proportional Evaluations To Shape The Teaching Workforce," Contemporary Economic Policy, Western Economic Association International, vol. 34(1), pages 47-62, January.
    15. Nils Gutacker & Andrew Street, 2018. "Multidimensional performance assessment of public sector organisations using dominance criteria," Health Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 13-27, February.
    16. Sulis, Isabella & Giambona, Francesca & Porcu, Mariano, 2020. "Adjusted indicators of quality and equity for monitoring the education systems over time. Insights on EU15 countries from PISA surveys," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    17. Pia Kjær Kristensen & Raquel Perez-Vicente & George Leckie & Søren Paaske Johnsen & Juan Merlo, 2020. "Disentangling the contribution of hospitals and municipalities for understanding patient level differences in one-year mortality risk after hip-fracture: A cross-classified multilevel analysis in Swed," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-14, June.
    18. Bosker, R.J. & van de Loo, P.J.E. & van der Velden, R.K.W., 1997. "Differential effects of colleges on the labour market success of their graduates," ROA Research Memorandum 1E, Maastricht University, Research Centre for Education and the Labour Market (ROA).
    19. Shimaa Elkomy & Graham Cookson, 2020. "Performance Management Strategy: Waiting Time in the English National Health Services," Public Organization Review, Springer, vol. 20(1), pages 95-112, March.
    20. Michael Kuhn & Luigi Siciliani, 2009. "Performance Indicators for Quality with Costly Falsification," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 18(4), pages 1137-1154, December.

    More about this item

    JEL classification:

    • I2 - Health, Education, and Welfare - - Education

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jorssa:v:172:y:2009:i:4:p:835-851. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.