IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v38y2004i4p425-433.html
   My bibliography  Save this article

Scaling for Residual Variance Components of Ordered Category Responses in Generalised Linear Mixed Multilevel Models

Author

Listed:
  • Antony Fielding

Abstract

No abstract is available for this item.

Suggested Citation

  • Antony Fielding, 2004. "Scaling for Residual Variance Components of Ordered Category Responses in Generalised Linear Mixed Multilevel Models," Quality & Quantity: International Journal of Methodology, Springer, vol. 38(4), pages 425-433, August.
  • Handle: RePEc:spr:qualqt:v:38:y:2004:i:4:p:425-433
    DOI: 10.1023/B:QUQU.0000043118.19835.6c
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1023/B:QUQU.0000043118.19835.6c
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1023/B:QUQU.0000043118.19835.6c?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. A. Fielding, 1999. "Why use arbitrary points scores?: ordered categories in models of educational progress," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(3), pages 303-328.
    2. Murray Aitkin, 1999. "A General Maximum Likelihood Analysis of Variance Components in Generalized Linear Models," Biometrics, The International Biometric Society, vol. 55(1), pages 117-128, March.
    3. Fielding, A., 1996. "On Scoring Ordered Classifications," Discussion Papers 96-10, Department of Economics, University of Birmingham.
    4. Fielding, A. & Yang, M., 1999. "Random Effects Models for Ordered Category Responses and Complex Structures in Educational Progress," Discussion Papers 99-20, Department of Economics, University of Birmingham.
    5. A. Fielding, 1999. "Why use arbitrary points scores?: ordered categories in models of educational progress," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(3), pages 303-328.
    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. Colin Vance & Rich Iovanna, 2008. "Cities and Satellites: Spatial Effects and Unobserved Heterogeneity in the Modeling of Urban Growth," Ruhr Economic Papers 0043, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    2. repec:zbw:rwirep:0043 is not listed on IDEAS
    3. Vance, Colin & Iovanna, Rich, 2008. "Cities and Satellites: Spatial Effects and Unobserved Heterogeneity in the Modeling of Urban Growth," Ruhr Economic Papers 43, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    4. Daniel Bauer, 2009. "A Note on Comparing the Estimates of Models for Cluster-Correlated or Longitudinal Data with Binary or Ordinal Outcomes," Psychometrika, Springer;The Psychometric Society, vol. 74(1), pages 97-105, March.

    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. Julian P. T. Higgins & Simon G. Thompson & David J. Spiegelhalter, 2009. "A re‐evaluation of random‐effects meta‐analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(1), pages 137-159, January.
    2. Getachew A. Dagne, 2016. "A growth mixture Tobit model: application to AIDS studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(7), pages 1174-1185, July.
    3. Marino, Maria Francesca & Alfó, Marco, 2016. "Gaussian quadrature approximations in mixed hidden Markov models for longitudinal data: A simulation study," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 193-209.
    4. Suzanne J Carroll & Michael J Dale & Theophile Niyonsenga & Anne W Taylor & Mark Daniel, 2020. "Associations between area socioeconomic status, individual mental health, physical activity, diet and change in cardiometabolic risk amongst a cohort of Australian adults: A longitudinal path analysis," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-16, May.
    5. Francesco BARTOLUCCI & Silvia BACCI & Claudia PIGINI, 2015. "A Misspecification Test for Finite-Mixture Logistic Models for Clustered Binary and Ordered Responses," Working Papers 410, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    6. Lluís Bermúdez & Dimitris Karlis & Isabel Morillo, 2020. "Modelling Unobserved Heterogeneity in Claim Counts Using Finite Mixture Models," Risks, MDPI, vol. 8(1), pages 1-13, January.
    7. Marco Alfo & Giovanni Trovato & Robert J. Waldmann, 2008. "Testing for country heterogeneity in growth models using a finite mixture approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(4), pages 487-514.
    8. Corrado, L. & Fingleton, B., 2011. "Multilevel Modelling with Spatial Effects," SIRE Discussion Papers 2011-13, Scottish Institute for Research in Economics (SIRE).
    9. Berg, Gerard J. van den & Uhlendorff, Arne & Wolff, Joachim, 2015. "Under heavy pressure : intense monitoring and accumulation of sanctions for young welfare recipients in Germany," IAB-Discussion Paper 201534, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    10. Caliendo, Marco & Künn, Steffen & Uhlendorff, Arne, 2016. "Earnings exemptions for unemployed workers: The relationship between marginal employment, unemployment duration and job quality," Labour Economics, Elsevier, vol. 42(C), pages 177-193.
    11. Marco Alfò & Stefano Caiazza & Giovanni Trovato, 2005. "Extending a Logistic Approach to Risk Modeling through Semiparametric Mixing," Journal of Financial Services Research, Springer;Western Finance Association, vol. 28(1), pages 163-176, October.
    12. Antonello Maruotti & Pierfrancesco Alaimo Di Loro, 2023. "CO2 emissions and growth: A bivariate bidimensional mean‐variance random effects model," Environmetrics, John Wiley & Sons, Ltd., vol. 34(5), August.
    13. Bruno Crepon & Marc Ferracci & Grégory Jolivet & Gerard Van Den Berg, 2010. "Analyzing the Anticipation of Treatments with Data on Notification Dates," Working Papers 2010-41, Center for Research in Economics and Statistics.
    14. Staudenmayer, John & Ruppert, David & Buonaccorsi, John P., 2008. "Density Estimation in the Presence of Heteroscedastic Measurement Error," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 726-736, June.
    15. Caffo, Brian & An, Ming-Wen & Rohde, Charles, 2007. "Flexible random intercept models for binary outcomes using mixtures of normals," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5220-5235, July.
    16. repec:jss:jstsof:08:i09 is not listed on IDEAS
    17. Marco Alfò & Giovanni Trovato, 2004. "Semiparametric Mixture Models for Multivariate Count Data, with Application," CEIS Research Paper 51, Tor Vergata University, CEIS.
    18. Brown, Sarah & Taylor, Karl & Wheatley Price, Stephen, 2005. "Debt and distress: Evaluating the psychological cost of credit," Journal of Economic Psychology, Elsevier, vol. 26(5), pages 642-663, October.
    19. Gerard J Van Den Berg & Barbara Hofmann & Arne Uhlendorff, 2016. "The Role of Sickness in the Evaluation of Job Search Assistance and Sanctions," Working Papers 2016-17, Center for Research in Economics and Statistics.
    20. Bergemann, Annette & Pohlan, Laura & Uhlendorff, Arne, 2016. "Job Creation Schemes in Turbulent Times," IZA Discussion Papers 10369, Institute of Labor Economics (IZA).
    21. A. Fielding, 1993. "Scoring functions for ordered classifications in statistical analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 27(1), pages 1-17, February.

    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:spr:qualqt:v:38:y:2004:i:4:p:425-433. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.