CLAug 26, 2013
Linear models and linear mixed effects models in R with linguistic applications
arXiv:1308.5499v1627 citations
Originality Synthesis-oriented
AI Analysis
It provides an incremental tutorial for linguists and researchers using R to apply mixed effects models to phonetic data.
The paper introduces linear mixed effects models in R for linguistic data analysis, focusing on voice pitch data to demonstrate modeling techniques including random intercepts and slopes.
This text is a conceptual introduction to mixed effects modeling with linguistic applications, using the R programming environment. The reader is introduced to linear modeling and assumptions, as well as to mixed effects/multilevel modeling, including a discussion of random intercepts, random slopes and likelihood ratio tests. The example used throughout the text focuses on the phonetic analysis of voice pitch data.