IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v42y1993i2p381-400.html
   My bibliography  Save this article

Interpretation of Transformed Axes in Multivariate Analysis

Author

Listed:
  • G. M. Arnold
  • A. J. Collins

Abstract

Several multivariate statistical techniques involve an orthogonal transformation to new axes. These lead to new co‐ordinates of a configuration usually in a lower dimensional space. Often it is desirable to interpret this new co‐ordination in terms of the original variables. In surveying some of the principles involved in achieving this aim, the use of projections is contrasted with the use of correlations. Cumulative sum diagrams are introduced as informative in the interpretation. The methods are illustrated for principal components analysis, factor analysis and generalized Procrustes analysis by using examples from sensory profiling and the development of psychological scales.

Suggested Citation

  • G. M. Arnold & A. J. Collins, 1993. "Interpretation of Transformed Axes in Multivariate Analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 42(2), pages 381-400, June.
    • Handle: RePEc:bla:jorssc:v:42:y:1993:i:2:p:381-400
    DOI: 10.2307/2986240
    as

    Download full text from publisher

    File URL: https://doi.org/10.2307/2986240
    Download Restriction: no
    File URL: https://libkey.io/10.2307/2986240?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
    ---><---

    Citations

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


    Cited by:

    1. Chae, Seong S. & Warde, William D., 2006. "Effect of using principal coordinates and principal components on retrieval of clusters," Computational Statistics & Data Analysis, Elsevier, vol. 50(6), pages 1407-1417, March.
    2. Jacques Bénasséni & Mohammed Bennani Dosse, 2012. "Analyzing multiset data by the Power STATIS-ACT method," 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. 6(1), pages 49-65, April.

    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:jorssc:v:42:y:1993:i:2:p:381-400. 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: 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.