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http://dx.doi.org/10.5351/KJAS.2010.23.6.1169

Simulation Study on Model Selection Based on AIC under Unbalanced Design in Linear Mixed Effect Models  

Lee, Yong-Hee (Department of Statistics, University of Seoul)
Publication Information
The Korean Journal of Applied Statistics / v.23, no.6, 2010 , pp. 1169-1178 More about this Journal
Abstract
This article consider a performance model selection based on AIC under unbalanced deign in linear mixed effect models. Vaida and Balanchard (2005) proposed conditional AIC for model selection in linear mixed effect models when the prediction of random effects is of primary interest. Theoretical properties of cAIC and related criteria have been investigated by Liang et al. (2008) and Greven and Kneib (2010). However, all of the simulation studies were performed under a balanced design. Even though functional form of AIC remain same even under the unbalanced deign, it is worthwhile to investigate performance of AIC based model selection criteria under the unbalanced design. The simulation study in this article shows how unbalancedness affects model selection in linear mixed effect models.
Keywords
Linear mixed effect models; unbalanced design; AIC; model selection;
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