Hierarchical Linear Modeling with Qualitative Data that Have Been Quantitized

This chapter explores Hierarchical Linear Modeling (HLM) with Qualitative Data, technical outline of the HLM, empirical demonstration and idea for suggested applications. It extends upon the idea of using quantitized data as dependent variables in regression models, but now the people deal with the case where data exist within a hierarchy. The chapter summarizes the following two key points: qualitative data can be quantified and, therefore, be subject to statistical modeling and it is critical to understand that hierarchies (or multiple levels/nesting) exist, especially in the social sciences. At the end of the consultant focus group, the consultants were given a homework assignment. They were asked by the researchers to identify a list of schools and districts in their regions that could be classified as “low implementers.” The chapter closes with an overview of strengths and limitations of the HLM.