Curtin University Homepage
  • Library
  • Help
    • Admin

    espace - Curtin’s institutional repository

    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item

    Influence diagnostics for random effect survival models: Application to a recurrent infection study for kidney patients on portable dialysis

    Access Status
    Fulltext not available
    Authors
    Xiang, L.
    Yau, K.
    Tse, S.
    Lee, Andy
    Date
    2007
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Xiang, L. and Yau, K. and Tse, S. and Lee, A. 2007. Influence diagnostics for random effect survival models: Application to a recurrent infection study for kidney patients on portable dialysis. Computational Statistics and Data Analysis. 51 (12): pp. 5977-5993.
    Source Title
    Computational Statistics and Data Analysis
    DOI
    10.1016/j.csda.2006.11.023
    ISSN
    01679473
    School
    School of Public Health
    URI
    http://hdl.handle.net/20.500.11937/8936
    Collection
    • Curtin Research Publications
    Abstract

    In modeling multivariate failure time data, a class of survival model with random effects is applicable. It incorporates the random effect terms in the linear predictor and includes various random effect survival models as special cases, such as the random effect model assuming Cox's proportional hazards, with Weibull baseline hazards and with power family of transformation in the relative risk function. Residual maximum likelihood (REML) estimation of parameters is achieved by adopting the generalised linear mixed models (GLMM) approach. Accordingly, influence diagnostics are developed as sensitivity measures for the REML estimation of model parameters. A data set of recurrent infections of kidney patients on portable dialysis illustrates the usefulness of the influence diagnostics. A simulation study is carried out to examine the performance of the proposed influence diagnostics.

    Related items

    Showing items related by title, author, creator and subject.

    • Some applications of local influence diagnostics.
      Yick, John S. (2000)
      The influence of observations on the outcome of an analysis is of importance in statistical data analysis. A practical and well-established approach to influence analysis is case deletion. However, it has its draw-backs ...
    • Diagnosis telling in people with psychosis
      Milton, A.; Mullan, Barbara (2014)
      Purpose of review: There are complexities in communicating diagnostic information relating to schizophrenia spectrum disorders. There is a current dearth of research in understanding how clinicians effectively communicate ...
    • Unsupervised Process Fault Detection with Random Forests
      Auret, L.; Aldrich, Chris (2010)
      Process monitoring technology plays a vital role in the automation of mineral processing plants, where there is an increased emphasis on safe, cost-effective, and environmentally responsible operation. Members of an ...
    Advanced search

    Browse

    Communities & CollectionsIssue DateAuthorTitleSubjectDocument TypeThis CollectionIssue DateAuthorTitleSubjectDocument Type

    My Account

    Admin

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Follow Curtin

    • 
    • 
    • 
    • 
    • 

    CRICOS Provider Code: 00301JABN: 99 143 842 569TEQSA: PRV12158

    Copyright | Disclaimer | Privacy statement | Accessibility

    Curtin would like to pay respect to the Aboriginal and Torres Strait Islander members of our community by acknowledging the traditional owners of the land on which the Perth campus is located, the Whadjuk people of the Nyungar Nation; and on our Kalgoorlie campus, the Wongutha people of the North-Eastern Goldfields.