IDEAS home Printed from https://ideas.repec.org/a/ids/ijpqma/v27y2019i2p161-176.html
   My bibliography  Save this article

Phase II monitoring of the nominal logistic regression profiles based on Wald and Rao score test statistics (a case study in healthcare: diabetic patients)

Author

Listed:
  • Kasra Jahani
  • Hamidreza Feili
  • Fereydon Ohadi

Abstract

In many statistical process monitoring (SPM), quality of process or product describes by a relationship between one or more predictor variable(s) and a nominal response variable called nominal logistic regression profile (NLRP). In this paper, two control charts including Wald and Rao score test (RST) is developed to monitor NLRP in Phase II. In addition, to evaluate the parameter estimation effect on the performance of control charts, maximum likelihood estimation (MLE) is developed in Phase I. Performance of the proposed control charts are evaluated using some simulation studies and results show that Wald control chart has better performance than RST chart under different shifts in NLRP parameters. Furthermore, to show the efficiency of the proposed approaches in real application, a case study in health-care is applied. Real case results is also showed that Wald control chart has better performance in faster detecting the out-of-control condition.

Suggested Citation

  • Kasra Jahani & Hamidreza Feili & Fereydon Ohadi, 2019. "Phase II monitoring of the nominal logistic regression profiles based on Wald and Rao score test statistics (a case study in healthcare: diabetic patients)," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 27(2), pages 161-176.
    • Handle: RePEc:ids:ijpqma:v:27:y:2019:i:2:p:161-176
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=100142
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Maryam Cheema & Muhammad Amin & Tahir Mahmood & Muhammad Faisal & Kamel Brahim & Ahmed Elhassanein, 2023. "Deviance and Pearson Residuals-Based Control Charts with Different Link Functions for Monitoring Logistic Regression Profiles: An Application to COVID-19 Data," Mathematics, MDPI, vol. 11(5), pages 1-13, February.

    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:ids:ijpqma:v:27:y:2019:i:2:p:161-176. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=177 .

    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.