IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-00477167.html
   My bibliography  Save this paper

How to Deal with Missing Categorical Data: Test of a Simple Bayesian Method

Author

Listed:
  • Thomas Astebro

    (Joseph L. Rotman School of Management - University of Toronto)

  • Gongyue Chen

    (University of Waterloo [Waterloo])

Abstract

The authors analyze the efficiency of six missing data techniques for categorical item nonresponse under the assumption that data are missing at random or missing completely at random. By efficiency, the authors mean a procedure that produces an unbiased estimate of true sample properties that is also easy to implement. The investigated techniques include listwise deletion, mode substitution, random imputation, two regression imputations, and a Bayesian model-based procedure. The authors analyze efficiency under six experimental conditions for a survey-based data set. They find that listwise deletion is efficient for the data analyzed. If data loss due to listwise deletion is an issue, the analysis points to the Bayesian method. Regression imputation is also efficient, but the result is conditioned on the specific data structure and may not hold in general. Additional problems arise when using regression imputation, making it less appropriate.

Suggested Citation

  • Thomas Astebro & Gongyue Chen, 2003. "How to Deal with Missing Categorical Data: Test of a Simple Bayesian Method," Post-Print hal-00477167, HAL.
    • Handle: RePEc:hal:journl:hal-00477167
    DOI: 10.1177/1094428103254672
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Toktaş-Palut, Peral & Baylav, Ecem & Teoman, Seyhan & Altunbey, Mustafa, 2014. "The impact of barriers and benefits of e-procurement on its adoption decision: An empirical analysis," International Journal of Production Economics, Elsevier, vol. 158(C), pages 77-90.
    2. Refait-Alexandre, Catherine & Serve, Stéphanie, 2020. "Multiple banking relationships: Do SMEs mistrust their banks?," Research in International Business and Finance, Elsevier, vol. 51(C).
    3. Ferrari, Pier Alda & Annoni, Paola & Barbiero, Alessandro & Manzi, Giancarlo, 2011. "An imputation method for categorical variables with application to nonlinear principal component analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2410-2420, July.
    4. Alireza Motaghifard & Manouchehr Omidvari & Abolfazl Kazemi, 2023. "Forecasting of safe-green buildings using decision tree algorithm: data mining approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(9), pages 10323-10350, September.
    5. Åstebro, Thomas & Thompson, Peter, 2011. "Entrepreneurs, Jacks of all trades or Hobos?," Research Policy, Elsevier, vol. 40(5), pages 637-649, June.
    6. Astebro, Thomas & Bernhardt, Irwin, 2003. "Start-up financing, owner characteristics, and survival," Journal of Economics and Business, Elsevier, vol. 55(4), pages 303-319.

    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:hal:journl:hal-00477167. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.