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Vol.32 No.2

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Linear Mixed-Effects Model for Analyzing Experimental Data

The Korean Journal of Cognitive and Biological Psychology / The Korean Journal of Cognitive and Biological Psychology, (P)1226-9654; (E)2733-466X
2020, v.32 no.2, pp.197-211
https://doi.org/10.22172/cogbio.2020.32.2.006

(2020). Linear Mixed-Effects Model for Analyzing Experimental Data. The Korean Journal of Cognitive and Biological Psychology, 32(2), 197-211, https://doi.org/10.22172/cogbio.2020.32.2.006

Abstract

This paper introduces a linear mixed-effects model with crossed random effects as an alternative to repeated measures analysis of variance (RM-ANOVA). With lmer function in the lme4 package, one of the R packages, two kinds of the linear mixed-effects model are described regarding the model specification, an estimation method, model comparison criteria, and an inference method. The use of the linear mixed-effects model is illustrated through an empirical example data. The performance of hypothesis testing is compared via a Monte Carlo simulation study between the mixed-effects model and variance of analysis framework.

keywords
linear mixed-effects model, F1/F2 analysis, R package, repeated-measures ANOVA, 선형 혼합효과 모형, F1/F2분석, R패키지, 반복측정 변량분석

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