[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/bla/anzsta/v44y2002i4p489-501.html
   My bibliography  Save this article

Estimation in Semiparametric Marginal Shared Gamma Frailty Models

Author

Listed:
  • Hien T.V. Vu
  • Matthew W. Knuiman
Abstract
The semiparametric marginal shared frailty models in survival analysis have the non–parametric hazard functions multiplied by a random frailty in each cluster, and the survival times conditional on frailties are assumed to be independent. In addition, the marginal hazard functions have the same form as in the usual Cox proportional hazard models. In this paper, an approach based on maximum likelihood and expectation–maximization is applied to semiparametric marginal shared gamma frailty models, where the frailties are assumed to be gamma distributed with mean 1 and variance θ. The estimates of the fixed–effect parameters and their standard errors obtained using this approach are compared in terms of both bias and efficiency with those obtained using the extended marginal approach. Similarly, the standard errors of our frailty variance estimates are found to compare favourably with those obtained using other methods. The asymptotic distribution of the frailty variance estimates is shown to be a 50–50 mixture of a point mass at zero and a truncated normal random variable on the positive axis for θ0 = 0. Simulations demonstrate that, for θ0

Suggested Citation

  • Hien T.V. Vu & Matthew W. Knuiman, 2002. "Estimation in Semiparametric Marginal Shared Gamma Frailty Models," Australian & New Zealand Journal of Statistics, Australian Statistical Publishing Association Inc., vol. 44(4), pages 489-501, December.
    • Handle: RePEc:bla:anzsta:v:44:y:2002:i:4:p:489-501
    DOI: 10.1111/1467-842X.00250
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1467-842X.00250
    Download Restriction: no
    File URL: https://libkey.io/10.1111/1467-842X.00250?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Guillaume Horny, 2009. "Inference in mixed proportional hazard models with K random effects," Statistical Papers, Springer, vol. 50(3), pages 481-499, June.
    2. Vu, Hien T. V., 2004. "Estimation in semiparametric conditional shared frailty models with events before study entry," Computational Statistics & Data Analysis, Elsevier, vol. 45(3), pages 621-637, April.

    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:bla:anzsta:v:44:y:2002:i:4:p:489-501. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=1369-1473 .

    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.