# Fixed and random effects selection in mixed effects models.

@article{Ibrahim2011FixedAR, title={Fixed and random effects selection in mixed effects models.}, author={J. Ibrahim and H. Zhu and Ramon I. Garcia and Ruixin Guo}, journal={Biometrics}, year={2011}, volume={67 2}, pages={ 495-503 } }

We consider selecting both fixed and random effects in a general class of mixed effects models using maximum penalized likelihood (MPL) estimation along with the smoothly clipped absolute deviation (SCAD) and adaptive least absolute shrinkage and selection operator (ALASSO) penalty functions. The MPL estimates are shown to possess consistency and sparsity properties and asymptotic normality. A model selection criterion, called the IC(Q) statistic, is proposed for selecting the penalty… Expand

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