The Problem While nested structures occur naturally in organizational and educational settings, past research has failed to recognize these nested structures. Ordinary least squares (OLS) methods assume independence of observation, fixing the intercepts and slopes across all groups. By not accounting for nested structures, errors of inference can occur with the risk of compromising the validity of the results. The Solution As new theories become more complex multilevel representations of phenomena, testing these complex theories require hierarchical linear modeling (HLM). HLM provides human resource development (HRD) practitioners with a better method to test multilevel theories while taking into account nested structures, providing a more accurate representation across the different levels. The Stakeholders The intended audience includes HRD scholars, scholar-practitioners, and students interested in testing multilevel theories, conducting research using HLM, or those who are involved in reviewing/editing HLM research articles.
