IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v30y2003i7p827-841.html
   My bibliography  Save this article

Residuals from deletion in added variable plots

Author

Listed:
  • A. H. M. Rahmatullah Imon

Abstract

An added variable plot is a commonly used plot in regression diagnostics. The rationale for this plot is to provide information about the addition of a further explanatory variable to the model. In addition, an added variable plot is most often used for detecting high leverage points and influential data. So far as we know, this type of plot involves the least squares residuals which, we suspect, could produce a confusing picture when a group of unusual cases are present in the data. In this situation, added variable plots may not only fail to detect the unusual cases but also may fail to focus on the need for adding a further regressor to the model. We suggest that residuals from deletion should be more convincing and reliable in this type of plot. The usefulness of an added variable plot based on residuals from deletion is investigated through a few examples and a Monte Carlo simulation experiment in a variety of situations.

Suggested Citation

  • A. H. M. Rahmatullah Imon, 2003. "Residuals from deletion in added variable plots," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(7), pages 827-841.
    • Handle: RePEc:taf:japsta:v:30:y:2003:i:7:p:827-841
    DOI: 10.1080/0266476032000076083
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/0266476032000076083
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/0266476032000076083?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.

    Citations

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


    Cited by:

    1. A.H.M. Rahmatullah Imon, 2009. "Deletion residuals in the detection of heterogeneity of variances in linear regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(3), pages 347-358.
    2. Ekele Alih & Hong Choon Ong, 2015. "Cluster-based multivariate outlier identification and re-weighted regression in linear models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(5), pages 938-955, May.
    3. Ekele Alih & Hong Choon Ong, 2015. "An outlier-resistant test for heteroscedasticity in linear models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(8), pages 1617-1634, August.
    4. Li-Chu Chien, 2011. "A robust diagnostic plot for explanatory variables under model mis-specification," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(1), pages 113-126.

    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:taf:japsta:v:30:y:2003:i:7:p:827-841. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.