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HLM stands for "Hierarchical Linear Modeling" and describes statistical methods for the analysis of hierarchically structured data. Sociological and psychological studies are often based on nested data structures. Each of the nested levels is represented by a separate model. Easy to handle, HLM enables you to create quickly and easily nested models. HLM allows for multilevel models to analyze simultaneously hierarchically structured data.
Why you should use HLM:
- Applicable to measured, counted as well as ordinally and nominally scaled variables
- Modeling of a functional relationship between the expected value, the target variable and a linear combination of explanatory variables
- Longitudinal analyzes and repeated measuring experiments