IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-1-4757-5654-8_39.html
   My bibliography  Save this book chapter

Assessing Gamma Frailty Models for Clustered Failure Time Data

In: Lifetime Data: Models in Reliability and Survival Analysis

Author

Listed:
  • Joanna H. Shih

    (National Heart, Lung, and Blood Institute, Biostatistics Research Branch
    University of Minnesota School of Public Health, Division of Biostatistics)

  • Thomas A. Louis

    (National Heart, Lung, and Blood Institute, Biostatistics Research Branch
    University of Minnesota School of Public Health, Division of Biostatistics)

Abstract

Proportional hazards frailty models use a random effect, so called frailty, to construct association for clustered failure time data. It is customary to assume that the random frailty follows a gamma distribution. In this paper, we propose a graphical method for assessing adequacy of the proportional hazards frailty models. In particular, we focus on the assessment of the gamma distribution assumption for the frailties. We calculate the average of the posterior expected frailties at several followup time points and compare it at these time points to 1, the known mean frailty. Large discrepancies indicate lack of fit. To aid in assessing the goodness of fit, we derive and estimate the standard error of the mean of the posterior expected frailties at each time point examined. We give an example to illustrate the proposed methodology.

Suggested Citation

  • Joanna H. Shih & Thomas A. Louis, 1996. "Assessing Gamma Frailty Models for Clustered Failure Time Data," Springer Books, in: Nicholas P. Jewell & Alan C. Kimber & Mei-Ling Ting Lee & G. A. Whitmore (ed.), Lifetime Data: Models in Reliability and Survival Analysis, pages 299-305, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4757-5654-8_39
    DOI: 10.1007/978-1-4757-5654-8_39
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    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:spr:sprchp:978-1-4757-5654-8_39. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.