Model selection can be defined as the task of estimating the performance of dif- ferent models in order to choose the (approximate) best one. The purpose of this article is to introduce an extension of the graphical representation of deviance proposed in the framework of classical and generalized linear models to the wider class of mixed models. The proposed plot is useful in determining which are the important explanatory variables conditioning on the random effects part. The applicability and the easy interpretation of the graph are illus- trated with a real data examples.
Sciandra, M. (2014). Variable selection in mixed models: a graphical approach. In 47th Scientific Meeting of the Italian Statistical Society Cagliari - June 11/13, 2014 Proceedings. Cagliari : CUEC Cooperativa Universitaria Editrice Cagliaritana.
Variable selection in mixed models: a graphical approach
SCIANDRA, Mariangela
2014-01-01
Abstract
Model selection can be defined as the task of estimating the performance of dif- ferent models in order to choose the (approximate) best one. The purpose of this article is to introduce an extension of the graphical representation of deviance proposed in the framework of classical and generalized linear models to the wider class of mixed models. The proposed plot is useful in determining which are the important explanatory variables conditioning on the random effects part. The applicability and the easy interpretation of the graph are illus- trated with a real data examples.
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