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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
4초록
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
- 발행일
- 2019-03
- 저널명
- 영어학
- 권
- 19
- 호
- 1
- 페이지
- 76 ~ 94
- 언어
- KOR
- 출판사
- 한국영어학회
- 발행국가
- 대한민국
- 분량
- 19 페이지
- ISSN
- E 2586-7474
P 1598-1398