Power family of transformation for Cox's regression with random effects

Kelvin K.W. Yau*, C. A. McGilchrist

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    3 Citations (Scopus)

    Abstract

    A random effect survival model with Box-Cox type relative risk function is proposed. It extends the model considered in McGilchrist (1993) by allowing the relative risk function to belong to a power family of transformations. This power family chooses the exponential relative risk function when the transformation parameter (k) tends to zero and the linear hazard when k equals one. Optimal value of k is obtained by maximizing an appropriate log-likelihood function. The proposed scheme is used to analyse two sets of multivariate failure time data. One data set confirms the choice of exponential relative risk function while the other concludes that the usual exponential specification is not optimal.

    Original languageEnglish
    Pages (from-to)57-66
    Number of pages10
    JournalComputational Statistics and Data Analysis
    Volume30
    Issue number1
    DOIs
    Publication statusPublished - 28 Mar 1999

    Fingerprint

    Dive into the research topics of 'Power family of transformation for Cox's regression with random effects'. Together they form a unique fingerprint.

    Cite this