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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Year of publication:	2001
Authors:	Adimari, Gianfranco ; Ventura, Laura
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 55.2001, 4, p. 413-419
Publisher:	Elsevier
Keywords:	Likelihood ratio test Logistic regression M-estimator Quasi-likelihood Robustness

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005254860