IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v48y2019i1p141-164.html
   My bibliography  Save this article

The use of components’ weights improves the diagnostic accuracy of a health-related index

Author

Listed:
  • Fragkiskos G. Bersimis
  • Demosthenes Panagiotakos
  • Malvina Vamvakari

Abstract

This work aims to evaluate whether the use of specific weights in each component of a health-related index, is associated with its diagnostic accuracy. In addition, the impact of a composite health-related index's components multitude is examined in relation to its classification ability. An un-weighted and various weighted indices were constructed using different weighting methods. The indices’ diagnostic ability was evaluated by using true positive rate, true negative rate, true rate, positive predictive value, negative predictive value and the area under the receiver operating characteristic curve. Weights used in this study were obtained from linear discriminant analysis and binary logistic regression. These indices were applied in both simulated and actual data; and a variety of scenarios was applied based on the distribution's parameters of the component variables and on the number of components used. Results indicate that weighted indices’ evaluation measures were significantly higher compared to the un-weighted one; whereas area under receiver operating characteristic curve was positively associated with the number of components of each index that were correlated with the outcome. Weighting of index's components, as well as greater number of components related to the investigated outcome should be recommended for the construction of accurate indices.

Suggested Citation

  • Fragkiskos G. Bersimis & Demosthenes Panagiotakos & Malvina Vamvakari, 2019. "The use of components’ weights improves the diagnostic accuracy of a health-related index," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(1), pages 141-164, January.
  • Handle: RePEc:taf:lstaxx:v:48:y:2019:i:1:p:141-164
    DOI: 10.1080/03610926.2017.1388401
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2017.1388401
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/03610926.2017.1388401?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.

    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:lstaxx:v:48:y:2019:i:1:p:141-164. 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/lsta .

    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.