IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v70y2005i1p99-122.html
   My bibliography  Save this article

Graphical representations and odds ratios in a distance-association model for the analysis of cross-classified data

Author

Listed:
  • Mark Rooij
  • Willem Heiser

Abstract

No abstract is available for this item.

Suggested Citation

  • Mark Rooij & Willem Heiser, 2005. "Graphical representations and odds ratios in a distance-association model for the analysis of cross-classified data," Psychometrika, Springer;The Psychometric Society, vol. 70(1), pages 99-122, March.
    • Handle: RePEc:spr:psycho:v:70:y:2005:i:1:p:99-122
    DOI: 10.1007/s11336-000-0848-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11336-000-0848-1
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11336-000-0848-1?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.

    Citations

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


    Cited by:

    1. Giuseppe Bove & Akinori Okada, 2018. "Methods for the analysis of asymmetric pairwise relationships," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(1), pages 5-31, March.
    2. Robin, Geneviève & Josse, Julie & Moulines, Éric & Sardy, Sylvain, 2019. "Low-rank model with covariates for count data with missing values," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 416-434.
    3. Saburi, S. & Chino, N., 2008. "A maximum likelihood method for an asymmetric MDS model," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4673-4684, June.
    4. Mark de Rooij, 2008. "The analysis of change, Newton's law of gravity and association models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 137-157, January.
    5. Ida Camminatiello & Antonello D’Ambra & Luigi D’Ambra, 2022. "The association in two-way ordinal contingency tables through global odds ratios," METRON, Springer;Sapienza Università di Roma, vol. 80(1), pages 9-22, April.
    6. Lombardo, Rosaria & Camminatiello, Ida & D'Ambra, Antonello & Beh, Eric J., 2021. "Assessing the Italian tax courts system by weighted three-way log-ratio analysis," Socio-Economic Planning Sciences, Elsevier, vol. 73(C).
    7. Luca Rossi, 2020. "Callous-unemotionalTraits with Mental Disorders in Adolescents by Two-Way Log-Ratio Analysis," International Journal of Business and Social Research, LAR Center Press, vol. 10(4), pages 1-09, April.
    8. Aquino Llinares, Nieves, 2015. "Unfolding Analysis of Work Conditions Affecting Employees’ Health According to their Positions in the Area of Solid Waste || Análisis unfolding de las condiciones de trabajo que afectan la salud de lo," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 20(1), pages 53-63, December.
    9. Hailemichael M. Worku & Mark De Rooij, 2017. "Properties of Ideal Point Classification Models for Bivariate Binary Data," Psychometrika, Springer;The Psychometric Society, vol. 82(2), pages 308-328, June.
    10. Willem Heiser, 2004. "Geometric representation of association between categories," Psychometrika, Springer;The Psychometric Society, vol. 69(4), pages 513-545, December.
    11. Fithian, William & Josse, Julie, 2017. "Multiple correspondence analysis and the multilogit bilinear model," Journal of Multivariate Analysis, Elsevier, vol. 157(C), pages 87-102.

    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:psycho:v:70:y:2005:i:1:p:99-122. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.