Hierarchical linear models (HLM) are a type of model used for analyzing data in a clustered or nested structure. An example of such data is students who are nested within classrooms, which are nested within schools; in this situation, we would expect that students within a cluster, such as a classroom or school, would share some similarities due to their common environment. Hierarchical linear models are also known as multilevel models, random coefficient models, or random effects models. HLM can be used to analyze a variety of questions with either categorical or continuous dependent variables.