IDEAS home Printed from https://ideas.repec.org/p/pqs/wpaper/0012005.html
   My bibliography  Save this paper

Random Effects Cox Models: A Poisson Modelling Approach

Author

Listed:
  • Renjun Ma

    (Faculty of Medicine, University of Ottawa)

  • Daniel Krewski

    (School of Mathematics and Statistics, Carleton University, and Faculty of Medicine, University of Ottawa)

  • Richard T. Burnett

    (Faculty of Medicine, University of Ottawa, and Environmental Health Directorate, Health Canada)

Abstract

We propose a Poisson modelling approach to random effects Cox proportional hazards models. Specifically we describe methods of statistical inference for a class of random effects Cox models which accommodate a wide range of nested random effects distributions. The orthodox BLUP approach to random effects Poisson modeling techniques enables us to study this new class of models as a single class, rather than as a collection of unrelated models. The explicit expressions for the random effects given by our approach facilitate incorporation of relatively large number of random effects. An important feature of this approach is that the principal results depend only on the first and second moments of the unobserved random effects. The application of proposed methods is illustrated through the reanalysis of data on the time to failure (tumour onset) in an animal carcinogen esis experiment previously reported by Mantel and Ciminera (1979).

Suggested Citation

  • Renjun Ma & Daniel Krewski & Richard T. Burnett, 2000. "Random Effects Cox Models: A Poisson Modelling Approach," RePAd Working Paper Series lrsp-TRS338, Département des sciences administratives, UQO.
    • Handle: RePEc:pqs:wpaper:0012005
    as

    Download full text from publisher

    File URL: http://www.repad.org/ca/on/lrsp/TRS338.pdf
    File Function: First version, 2000
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Cox model; BLUP; estimating equation; frailty; generalized linear models; random effects; Tweedie exponential dispersion model;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General

    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:pqs:wpaper:0012005. 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: Christian Calmes (email available below). General contact details of provider: https://edirc.repec.org/data/dsuqoca.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.