Covariate Transformation Diagnostics for Generalized Linear Models

Andy H. Lee, John S. Yick

    Research output: Contribution to journalComment/debate


    Transformations of covariates are commonly applied in regression analysis. When a parametric transformation family is used, the maximum likelihood estimate of the transformation parameter is often sensitive to minor perturbations of the data. Diagnostics are derived to assess the influence of observations on the covariate transformation parameter in generalized linear models. Three numerical examples are presented to illustrate the usefulness of the proposed diagnostics.
    Original languageEnglish
    Pages (from-to)383-398
    Number of pages16
    JournalAnnals of the Institute of Statistical Mathematics
    Issue number2
    Publication statusPublished - 1999


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