Stratified Multilevel Graphical Models: a gender perspective in education

This study proposes a methodological approach to investigate gender disparities in education, particularly focusing on the schooling phase and its influence on career trajectories. The research applies multilevel linear models to analyse student performance concerning various factors, with a specific emphasis on gender-specific outcomes. The study aims to identify and test context-specific independencies that may impact 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 graphical models, to visualize and generalize the complex dependencies among covariates, random effects, and gender influences on educational outcomes.