혼합효과모형(Mixed-Effects Model)을 이용한 실험언어학 데이터 분석 방법 고찰: 자기조절읽기 실험 데이터를 중심으로

How to analyze experimental linguistic data using a mixed-effects model in R: Focusing on data from a self-paced reading experiment.
Citations

SCOPUS

4

초록

This study examined a practical use of mixed-effects models in R, analyzing accuracy and reading time data from a self-paced reading experiment. It discussed the applications of logistic mixed-effects model for binary data (e.g., accuracy data) and the use of a mixed-effects model for reading time (RT) data, effectively removing outliers within the data set. A sample for mixed-effects model analyses was collected from a previously conducted self-paced reading experiment, involving English reduced relative clauses for 30 advanced and intermediate second language learners. Rationales and guidelines toward selecting the most appropriate mixed-effects model and checking model assumptions were also discussed.

키워드

mixed-effects model; linear mixed model; logistic mixed model; experimental linguistics; psycholinguistics; self-paced reading; reading time; RT data; accuracy
제목
혼합효과모형(Mixed-Effects Model)을 이용한 실험언어학 데이터 분석 방법 고찰: 자기조절읽기 실험 데이터를 중심으로
제목 (타언어)
How to analyze experimental linguistic data using a mixed-effects model in R: Focusing on data from a self-paced reading experiment.
저자
신정아
DOI
10.15738/kjell.19.1.201903.76
발행일
2019-03
저널명
영어학
권
19
호
1
페이지
76 ~ 94