Hierarchical Linear Modeling

Hierarchical Linear Modeling (HLM), also called multilevel modeling, is a statistical method used to analyze data that’s organized in layers or groups—like students within classrooms or employees within companies. It recognizes that individuals are influenced both by their personal characteristics and by the larger group they belong to. HLM helps researchers understand how factors at different levels affect outcomes, accounting for the nested structure. This approach provides more accurate results by considering both individual variation and group-level differences, making it useful in education, social sciences, and health research to better understand complex, layered data.