Stratified multilevel graphical models: examining gender dynamics in education

This study proposes a methodological approach to investigate gender disparities in education, particularly focusing on the schooling phase, which has a crucial influence on career trajectories. The research employs multilevel linear models to analyze student performance concerning various factors, with a particular emphasis on gender-specific outcomes. The study aims to identify and test context-specific independencies that may reflect educational disparities between genders. The methodology includes the introduction of supplementary parameters in multilevel models to capture and examine these independencies. Furthermore, the research proposes encoding these novel relationships in graphical models, specifically stratified chain graph models, to visualize and generalize the complex dependencies among covariates, random effects, and gender influences on educational outcomes.