IDEAS home Printed from https://ideas.repec.org/p/hhs/cesisp/0114.html
   My bibliography  Save this paper

Performance Evaluation Based on the Robust Mahalanobis Distance and Multilevel Modelling Using Two New Strategies

Author

Listed:
  • Hussain, S

    (Division of Primary Care and General Practice, School of Medicine, University of Birmingham)

  • Mohamed, M. A.

    (Department of Public Health, University of Birmingham, UK)

  • Holder, R.

    (Division of Primary Care and General Practice, School of Medicine, University of Birmingham)

  • Almasri, A.

    (Department of Economics and Statistics, Karlstad University, Sweden)

  • Shukur, G

    (Jönköping International Business School)

Abstract

In this paper we propose a general framework for performance evaluation of organisations and individuals over time using routinely collected performance variables or indicators. Such variables or indicators are often correlated over time, with missing observations, and often come from heavy tailed distributions shaped by outliers. Two double robust strategies are used for evaluation (ranking) of sampling units. Strategy 1 can handle missing data using residual maximum likelihood (RML) at stage two, while strategy two handle missing data at stage one. Strategy 2 has the advantage that overcomes the problem of multicollinearity. Strategy one requires independent indicators for the construction of the distances, where strategy two does not. Two different domain examples are used to illustrate the application of the two strategies. Example one considers performance monitoring of gynaecologists and example two considers the performance of industrial firms.

Suggested Citation

  • Hussain, S & Mohamed, M. A. & Holder, R. & Almasri, A. & Shukur, G, 2008. "Performance Evaluation Based on the Robust Mahalanobis Distance and Multilevel Modelling Using Two New Strategies," Working Paper Series in Economics and Institutions of Innovation 114, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
  • Handle: RePEc:hhs:cesisp:0114
    as

    Download full text from publisher

    File URL: https://static.sys.kth.se/itm/wp/cesis/cesiswp114.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Ranking indicators; performance; robust statistics; multilevel estimation; Mahalanobis distance;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:hhs:cesisp:0114. 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: Vardan Hovsepyan (email available below). General contact details of provider: https://edirc.repec.org/data/cekthse.html .

    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.