• DocumentCode
    1997584
  • Title

    Outlier detection in logistic regression and its application in medical data analysis

  • Author

    Ahmad, Sahar ; Ramli, Norazan Mohamed ; Midi, H.

  • Author_Institution
    Fac. of Comput. & Math. Sci., Univ. Teknol. MARA, Shah Alam, Malaysia
  • fYear
    2012
  • fDate
    3-4 Dec. 2012
  • Firstpage
    503
  • Lastpage
    507
  • Abstract
    The application of logistic regression is widely used in medical research. The detection of outliers has become an essential part of logistic regression. It is often observed outliers have a considerable influence on the analysis results, which may lead the study to the wrong conclusions. Many procedures for the identification of outliers in logistic regression are available in the literature. In this paper, four methods for outlier detection have been investigated and compared through numerical examples.
  • Keywords
    biomedical engineering; data analysis; logistics; medical computing; regression analysis; logistic regression application; medical data analysis; medical research; outlier detection; detection; logistic regression; outlier; residual;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Humanities, Science and Engineering (CHUSER), 2012 IEEE Colloquium on
  • Conference_Location
    Kota Kinabalu
  • Print_ISBN
    978-1-4673-4615-3
  • Type

    conf

  • DOI
    10.1109/CHUSER.2012.6504365
  • Filename
    6504365