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ISSN : 1226-9654

논문 상세

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논문 투고

Vol.32 No.2

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실험데이터 분석을 위한 선형 혼합효과 모형

Linear Mixed-Effects Model for Analyzing Experimental Data

한국심리학회지: 인지 및 생물 / 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
이우열 (충북대학교)
이우열. (2020). 실험데이터 분석을 위한 선형 혼합효과 모형. 한국심리학회지: 인지 및 생물, 32(2), 197-211, https://doi.org/10.22172/cogbio.2020.32.2.006

초록

본 논문은 반복측정 변량분석의 대안으로서 교차 무선효과를 가진 선형 혼합효과 모형을 소개한다. 두 종류의 선형 혼합효과 모형의 설정, 추정방법, 모형 비교방법, 추론방법에 관해 R패키지 중 하나인 lme4 패키지의 lmer 함수를 가지고 설명한다. 예제데이터를 통해 선형 혼합효과 모형의 용례를 보인다. 또한, 몬테카를로 시뮬레이션 실험을 통해 특정 상황에서 선형 혼합효과 모형과 변량분석 사이에서 가설검정 수행을 비교한다.

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

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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