Hierarchical Linear Models

Hierarchical Linear Models (HLM), also known as multi-level models, are statistical tools used to analyze data that have a nested structure—like students within classrooms or employees within companies. They allow us to understand how factors at different levels influence outcomes simultaneously. For example, HLM can assess how student performance is affected both by individual characteristics and by classroom or school environment. This approach accounts for the dependencies in the data, providing more accurate insights into how different levels interact and influence results.