Generalized degrees of freedom and adaptive model selection in linear mixed-effects models

@article{Zhang2012GeneralizedDO,
  title={Generalized degrees of freedom and adaptive model selection in linear mixed-effects models},
  author={Bo Zhang and Xiaotong Shen and Kurunthachalam L Kannan},
  journal={Computational statistics & data analysis},
  year={2012},
  volume={56 3},
  pages={574-586}
}
Linear mixed-effects models involve fixed effects, random effects and covariance structure, which require model selection to simplify a model and to enhance its interpretability and predictability. In this article, we develop, in the context of linear mixed-effects models, the generalized degrees of freedom and an adaptive model selection procedure defined by a data-driven model complexity penalty. Numerically, the procedure performs well against its competitors not only in selecting fixed… CONTINUE READING