IDEAS home Printed from https://ideas.repec.org/a/spr/metrik/v81y2018i4d10.1007_s00184-018-0649-0.html
   My bibliography  Save this article

An algebraic generalisation of some variants of simple correspondence analysis

Author

Listed:
  • Eric J. Beh

    (University of Newcastle)

  • Rosaria Lombardo

    (University of Campania)

Abstract

For an analysis of the association between two categorical variables that are cross-classified to form a contingency table, graphical procedures have been central to this analysis. In particular, correspondence analysis has grown to be a popular method for obtaining such a summary and there is a great variety of different approaches that one may consider to perform. In this paper, we shall introduce a simple algebraic generalisation of some of the more common approaches to obtaining a graphical summary of association, where these approaches are akin to the correspondence analysis of a two-way contingency table. Specific cases of the generalised procedure include the classical and non-symmetrical correspondence plots and the symmetrical and isometric biplots.

Suggested Citation

  • Eric J. Beh & Rosaria Lombardo, 2018. "An algebraic generalisation of some variants of simple correspondence analysis," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(4), pages 423-443, May.
  • Handle: RePEc:spr:metrik:v:81:y:2018:i:4:d:10.1007_s00184-018-0649-0
    DOI: 10.1007/s00184-018-0649-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00184-018-0649-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00184-018-0649-0?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. Michel Velden & Henk A.L. Kiers, 2005. "Rotation in Correspondence Analysis," Journal of Classification, Springer;The Classification Society, vol. 22(2), pages 251-271, September.
    2. Vartan Choulakian, 1988. "Exploratory analysis of contingency tables by loglinear formulation and generalizations of correspondence analysis," Psychometrika, Springer;The Psychometric Society, vol. 53(2), pages 235-250, June.
    3. Lombardo, R. & Beh, E.J. & D'Ambra, L., 2007. "Non-symmetric correspondence analysis with ordinal variables using orthogonal polynomials," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 566-577, September.
    4. John Aitchison & Michael Greenacre, 2002. "Biplots of compositional data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 51(4), pages 375-392, October.
    5. Vartan Choulakian, 1988. "Exploratory analysis of contingency tables by loglinear formulation and generalizations of correspondence analysis," Psychometrika, Springer;The Psychometric Society, vol. 53(4), pages 593-593, December.
    6. Rosaria Lombardo & Eric Beh & Antonello D'Ambra, 2011. "Studying the dependence between ordinal-nominal categorical variables via orthogonal polynomials," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(10), pages 2119-2132.
    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. Carolyn J. Anderson & Stanley Wasserman, 1995. "Log-Multiplicative Models for Valued Social Relations," Sociological Methods & Research, , vol. 24(1), pages 96-127, August.
    2. Robert Kapłon, 2006. "A retrospective review of categorical data analysis – theory and marketing practice," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 16(1), pages 55-72.
    3. Carolyn Anderson, 1996. "The analysis of three-way contingency tables by three-mode association models," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 465-483, September.
    4. Siciliano, Roberta & Mooijaart, Ab, 1997. "Three-factor association models for three-way contingency tables," Computational Statistics & Data Analysis, Elsevier, vol. 24(3), pages 337-356, May.
    5. Shizuhiko Nishisato, 1996. "Gleaning in the field of dual scaling," Psychometrika, Springer;The Psychometric Society, vol. 61(4), pages 559-599, December.
    6. André Carlier & Pieter Kroonenberg, 1996. "Decompositions and biplots in three-way correspondence analysis," Psychometrika, Springer;The Psychometric Society, vol. 61(2), pages 355-373, June.
    7. B. Baris Alkan & Afsin Sahin, 2011. "Measuring inequalities in the distribution of health workers by bi-plot approach: The case of Turkey," Journal of Economics and Behavioral Studies, AMH International, vol. 2(2), pages 57-66.
    8. Michael Greenacre, 2016. "Selection and statistical analysis of compositional ratios," Economics Working Papers 1551, Department of Economics and Business, Universitat Pompeu Fabra.
    9. Giovanni C. Porzio & Giancarlo Ragozini & Domenico Vistocco, 2008. "On the use of archetypes as benchmarks," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 419-437, September.
    10. Javier Palarea-Albaladejo & Josep Martín-Fernández & Jesús Soto, 2012. "Dealing with Distances and Transformations for Fuzzy C-Means Clustering of Compositional Data," Journal of Classification, Springer;The Classification Society, vol. 29(2), pages 144-169, July.
    11. Michael Greenacre & Paul Lewi, 2005. "Distributional equivalence and subcompositional coherence in the analysis of contingency tables, ratio-scale measurements and compositional data," Economics Working Papers 908, Department of Economics and Business, Universitat Pompeu Fabra, revised Aug 2007.
    12. Anna Maria Fiori & Francesco Porro, 2023. "A compositional analysis of systemic risk in European financial institutions," Annals of Finance, Springer, vol. 19(3), pages 325-354, September.
    13. Blasius, J. & Greenacre, M. & Groenen, P.J.F. & van de Velden, M., 2009. "Special issue on correspondence analysis and related methods," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3103-3106, June.
    14. Dawn Iacobucci & Doug Grisaffe, 2018. "Perceptual maps via enhanced correspondence analysis: representing confidence regions to clarify brand positions," Journal of Marketing Analytics, Palgrave Macmillan, vol. 6(3), pages 72-83, September.
    15. Germ`a Coenders & N'uria Arimany Serrat, 2023. "Accounting statement analysis at industry level. A gentle introduction to the compositional approach," Papers 2305.16842, arXiv.org, revised Sep 2024.
    16. Juan José Egozcue & Vera Pawlowsky-Glahn, 2019. "Rejoinder on: Compositional data: the sample space and its structure," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 658-663, September.
    17. Marco Taussi & Caterina Gozzi & Orlando Vaselli & Jacopo Cabassi & Matia Menichini & Marco Doveri & Marco Romei & Alfredo Ferretti & Alma Gambioli & Barbara Nisi, 2022. "Contamination Assessment and Temporal Evolution of Nitrates in the Shallow Aquifer of the Metauro River Plain (Adriatic Sea, Italy) after Remediation Actions," IJERPH, MDPI, vol. 19(19), pages 1-24, September.
    18. Siham Zaaboubi & Lotfi Khiari & Salah Abdesselam & Jacques Gallichand & Fassil Kebede & Ghouati Kerrache, 2020. "Particle Size Imbalance Index from Compositional Analysis to Evaluate Cereal Sustainability for Arid Soils in Eastern Algeria," Agriculture, MDPI, vol. 10(7), pages 1-10, July.
    19. Gardner-Lubbe, Sugnet, 2016. "A triplot for multiclass classification visualisation," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 20-32.
    20. 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.

    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:metrik:v:81:y:2018:i:4:d:10.1007_s00184-018-0649-0. 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.