A Robust Approach to Longitudinal Data Analysis
نویسنده
چکیده
In this paper we introduce robust techniques for inference and model selection in the analysis of longitudinal data. Robust versions of quasi-likelihood functions are obtained by building upon a set of robust estimating equations where robustness is achieved by weighting the classical estimating equations. The robust quasi-likelihood functions are then used to construct a class of test statistics for model selection. We derive the asymptotic distribution of this class of test statistics, and show its robustness properties in terms of stability of the asymptotic level and power under contamination. We also address the problem of the robust estimation of the nuisance parameters. The application to a real dataset confirms the benefit of our robust analysis.
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