IDEAS home Printed from https://ideas.repec.org/p/zbw/sfb649/sfb649dp2008-012.html
   My bibliography  Save this paper

Visualizing exploratory factor analysis models

Author

Listed:
  • Klinke, Sigbert
  • Wagner, Cornelia

Abstract

Exploratory factor analysis (EFA) is an important tool in data analyses, particularly in social science. Usually four steps are carried out which contain an large number of options. One important option is the number of factors and the association of variables with a factor. Our tools aim to visualize various models with different numbers in parallel of factors and to analyze which consequences a specific option has. We apply our method to dats collected at the School of Business and Economics for evaluation of lectures by students. These data were analyzed by Zhou (2004) and Reichelt (2007).

Suggested Citation

  • Klinke, Sigbert & Wagner, Cornelia, 2008. "Visualizing exploratory factor analysis models," SFB 649 Discussion Papers 2008-012, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  • Handle: RePEc:zbw:sfb649:sfb649dp2008-012
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/25254/1/558751237.PDF
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Artür Manukyan & Erhan Çene & Ahmet Sedef & Ibrahim Demir, 2014. "Dandelion plot: a method for the visualization of R-mode exploratory factor analyses," Computational Statistics, Springer, vol. 29(6), pages 1769-1791, December.

    More about this item

    Keywords

    Factor analysis; visualization; questionnaire; evaluation of teaching;
    All these keywords.

    JEL classification:

    • C39 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Other
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:zbw:sfb649:sfb649dp2008-012. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/sohubde.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.