IDEAS home Printed from https://ideas.repec.org/a/bla/jorssa/v168y2005i1p159-183.html
   My bibliography  Save this article

Generalized linear mixed models for ordered responses in complex multilevel structures: effects beneath the school or college in education

Author

Listed:
  • Antony Fielding
  • Min Yang

Abstract

Summary. The complexities of educational processes and structure and the need for disentangling effects beneath the level of the school or college are discussed. Ordinal response multilevel crossed random‐effects models for educational grades are introduced. Weighted random effects for teacher contributions are then added. Estimation methodology is reviewed. Specially written macros for quasi‐likelihood with second‐order terms are described. The application discusses General Certificate of Education at advanced level grades cross‐classified by student and teaching group within a number of institutions. The methods handle teacher effects where several teachers contribute to provision and where each teacher deals with several groups. Some methodological lessons are drawn for sparse data and the use of extra‐multinomial variation. Developments of the analysis yield conclusions about the sources of variation in educational progress, and particularly the effect of teachers.

Suggested Citation

  • Antony Fielding & Min Yang, 2005. "Generalized linear mixed models for ordered responses in complex multilevel structures: effects beneath the school or college in education," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(1), pages 159-183, January.
    • Handle: RePEc:bla:jorssa:v:168:y:2005:i:1:p:159-183
    DOI: 10.1111/j.1467-985X.2004.00342.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-985X.2004.00342.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-985X.2004.00342.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
    ---><---

    References listed on IDEAS

    as
    1. M. Yang & H. Goldstein & A. Heath, 2000. "Multilevel models for repeated binary outcomes: attitudes and voting over the electoral cycle," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 163(1), pages 49-62.
    2. Germán Rodríguez & Noreen Goldman, 2001. "Improved estimation procedures for multilevel models with binary response: a case‐study," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(2), pages 339-355.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. J. R. Lockwood & D. McCaffrey, 2020. "Using hidden information and performance level boundaries to study student–teacher assignments: implications for estimating teacher causal effects," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1333-1362, October.
    2. Chan, Moon-tong & Yu, Dalei & Yau, Kelvin K.W., 2015. "Multilevel cumulative logistic regression model with random effects: Application to British social attitudes panel survey data," Computational Statistics & Data Analysis, Elsevier, vol. 88(C), pages 173-186.
    3. George Leckie, 2009. "The complexity of school and neighbourhood effects and movements of pupils on school differences in models of educational achievement," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(3), pages 537-554, June.
    4. Philipp Ecken & Richard Pibernik, 2016. "Hit or Miss: What Leads Experts to Take Advice for Long-Term Judgments?," Management Science, INFORMS, vol. 62(7), pages 2002-2021, July.
    5. Pedro Luis do N. Silva & Fernando Antônio da S. Moura, 2022. "Fitting multivariate multilevel models under informative sampling," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1663-1678, October.

    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. Stephen Jivraj, 2012. "Modelling Socioeconomic Neighbourhood Change due to Internal Migration in England," Urban Studies, Urban Studies Journal Limited, vol. 49(16), pages 3565-3578, December.
    2. Weible, Daniela & Salamon, Petra & Christoph-Schulz, Inken B. & Peter, Guenter, 2013. "How do political, individual and contextual factors affect school milk demand? Empirical evidence from primary schools in Germany," Food Policy, Elsevier, vol. 43(C), pages 148-158.
    3. Guillaume Horny & Dragana Djurdjevic & Bernhard Boockmann & François Laisney, 2008. "Bayesian Estimation of Cox Models with Non-nested Random Effects: an Application to the Ratification Of ILO Conventions by Developing Countries," Annals of Economics and Statistics, GENES, issue 89, pages 193-214.
    4. Sun-Joo Cho & Paul Boeck & Susan Embretson & Sophia Rabe-Hesketh, 2014. "Additive Multilevel Item Structure Models with Random Residuals: Item Modeling for Explanation and Item Generation," Psychometrika, Springer;The Psychometric Society, vol. 79(1), pages 84-104, January.
    5. Getinet A. Haile, 2015. "Workplace Job Satisfaction in Britain: Evidence from Linked Employer–Employee Data," LABOUR, CEIS, vol. 29(3), pages 225-242, September.
    6. Seonho Shin, 2021. "Were they a shock or an opportunity?: The heterogeneous impacts of the 9/11 attacks on refugees as job seekers—a nonlinear multi-level approach," Empirical Economics, Springer, vol. 61(5), pages 2827-2864, November.
    7. Dana A. Glei & Noreen Goldman & German Rodriguez, 2002. "Utilization of Care During Pregnancy in Rural Guatemala: Does Obstetrical Need Matters," Working Papers 308, Princeton University, Woodrow Wilson School of Public and International Affairs, Office of Population Research..
    8. Jennifer Broatch & Sharon Lohr, 2012. "Multidimensional Assessment of Value Added by Teachers to Real-World Outcomes," Journal of Educational and Behavioral Statistics, , vol. 37(2), pages 256-277, April.
    9. Shane A Kavanagh & Julia M Shelley & Christopher Stevenson, 2018. "Is gender inequity a risk factor for men reporting poorer self-rated health in the United States?," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-15, July.
    10. Nkafu Anumendem & Bieke De Fraine & Patrick Onghena & Jan Van Damme, 2013. "The impact of coding time on the estimation of school effects," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(2), pages 1021-1040, February.
    11. Diana Miglioretti & Patrick Heagerty, 2004. "Marginal Modeling of Multilevel Binary Data with Time-Varying Covariates," UW Biostatistics Working Paper Series 1050, Berkeley Electronic Press.
    12. Rabe-Hesketh, Sophia & Skrondal, Anders & Pickles, Andrew, 2005. "Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects," Journal of Econometrics, Elsevier, vol. 128(2), pages 301-323, October.
    13. Sophia Rabe‐Hesketh & Anders Skrondal, 2006. "Multilevel modelling of complex survey data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(4), pages 805-827, October.
    14. 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.
    15. Bartolucci, Francesco & Nigro, Valentina, 2007. "Maximum likelihood estimation of an extended latent Markov model for clustered binary panel data," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3470-3483, April.
    16. S. Rabe-Hesketh & A. Skrondal & H. K. Gjessing, 2008. "Biometrical Modeling of Twin and Family Data Using Standard Mixed Model Software," Biometrics, The International Biometric Society, vol. 64(1), pages 280-288, March.
    17. Weible, Daniela & Burgelt, Doreen & Christoph, Inken B. & Peter, Guenter & Rothe, Andrea & Salamon, Petra & Weber, Sascha A., 2011. "School milk demand in Germany: The role of individual and contextual factors - preliminary results," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 115739, European Association of Agricultural Economists.
    18. L. Bryan, Mark & P. Jenkins, Stephen, 2013. "Regression analysis of country effects using multilevel data: a cautionary tale," ISER Working Paper Series 2013-14, Institute for Social and Economic Research.
    19. Van Oirbeek, R. & Lesaffre, E., 2012. "Assessing the predictive ability of a multilevel binary regression model," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1966-1980.
    20. Paula L. Griffiths & James J. Brown & Peter W. F. Smith, 2004. "A comparison of univariate and multivariate multilevel models for repeated measures of use of antenatal care in Uttar Pradesh," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(4), pages 597-611, November.

    More about this item

    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:168:y:2005:i:1:p:159-183. See general information about how to correct material in RePEc.

    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. RePEc uses bibliographic data supplied by the respective publishers.