Youran Lin, University of Alberta

In applied psycholinguistics, researchers often deal with complex factors that contribute to large variations – Such factors may be interrelated and contribute in a non-linear manner. Bilingual development is an issue of this nature. Through realistic bilingual datasets, this course will introduce a few statistical methods to account for such complexities. Participants will gain knowledge and experiences in (1) using directed acyclic graphs and structural equation modeling to account for complex
structural connections (e.g., mediation), and (2) using general additive modeling and variations of linear regression (e.g., quadratic regression) to account for non-linear associations. 

Prior knowledge: Familiarity with R and knowledge of linear regression

Participants should bring their own laptop and are welcome to bring their own datasets for practice. If you wish to practice with your own datasets, they should include continuous dependent variable(s), multiple independent variables with potential mediating relationships, and at least one continuous independent variable.