Abstract
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.
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Lee, A.H., Yick, J.S. Covariate Transformation Diagnostics for Generalized Linear Models. Annals of the Institute of Statistical Mathematics 51, 383–398 (1999). https://doi.org/10.1023/A:1003874628445
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DOI: https://doi.org/10.1023/A:1003874628445