A scalable and efficient covariate selection criterion for mixed effects regression models with unknown random effects structure

Abstract

A new model selection criterion for mixed effects regression models is introduced. The criterion is computable when the model is fitted with a two-step method and even when the structure and the distribution of the random effects are unknown. The criterion is especially useful in the early stage of the model building process when one needs to decide which… (More)
DOI: 10.1016/j.csda.2017.07.011

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Cite this paper

@article{Craiu2018ASA, title={A scalable and efficient covariate selection criterion for mixed effects regression models with unknown random effects structure}, author={Radu V. Craiu and Thierry Duchesne}, journal={Computational Statistics & Data Analysis}, year={2018}, volume={117}, pages={154-161} }