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http://dx.doi.org/10.5351/KJAS.2015.28.5.1035

Effect of Experimental Layout on Model Selection under Variance Components Models: A Simulation Study  

Lee, Yonghee (Department of Statistics, University of Seoul)
Publication Information
The Korean Journal of Applied Statistics / v.28, no.5, 2015 , pp. 1035-1046 More about this Journal
Abstract
Variance components models incorporate various random factors in the form of linear models. There are two experimental Layouts for the classification of factors under variance components models: nested classification and crossed classification. We consider two-way variance components models and investigate the effect of experimental Layout on the performance of model selection criteria AIC and BIC. The effect of experimental Layout is studied through a simulation study with various combinations of parameters in a systematic fashion. The simulation study shows differences in performance of model selection methods between the two classification. There is a particular tendency to prefer the smaller model than the true model when the variance component of a nested factor becomes relatively larger than a nesting factor that is persistent even when the sample size is not small.
Keywords
variance components models; linear mixed models; nested classification; crossed classification; model selection; AIC; BIC; experimental layout;
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