Robust inference for generalized linear models with application to logistic regression
In this paper we consider a suitable scale adjustment of the estimating function which defines a class of robust M-estimators for generalized linear models. This leads to a robust version of the quasi-profile loglikelihood which allows us to derive robust likelihood ratio type tests for inference and model selection having the standard asymptotic behaviour. An application to logistic regression is discussed.
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Volume (Year): 55 (2001)
Issue (Month): 4 (December)
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