Hierarchical Modeling

Hierarchical modeling is a statistical approach that analyzes data structured in multiple levels, capturing the relationships within and between groups. For example, studying student performance might involve individual student data, classroom influences, and school-level factors. By considering these layered levels simultaneously, hierarchical models provide more accurate insights, account for variability at each level, and help identify how different factors influence outcomes across different groups. It's like looking at the big picture while understanding the details within each smaller part, ensuring more nuanced and reliable analysis.