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

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.