Distinguishing the Trees from the Forest: Applying Cluster Analysis to Thematic Qualitative Data
Guest, Greg & McLellan, Eleanor (2003)
Field Methods, 15(2): 186-201
Qualitative data analysis requires organizing and synthesizing often large quantities of text. In many cases, this analysis entails negotiating the interplay between raw data, semantic themes or codes, and the overarching conceptual framework. In this article, the authors use a case study, which examines HIV vaccine efficacy trial participants' discourse, to demonstrate how cluster analysis can be used to aid in the analysis of large qualitative data sets. After briefly reviewing the systematic approaches to qualitative analysis and describing the project background, the authors present an example of how a hierarchical cluster technique can be incorporated into a multistage thematic analysis.
Cited by Macia
In this article I discuss cluster analysis as an exploratory tool to support the identification of associations within qualitative data. While not appropriate for all qualitative projects, cluster analysis can be particularly helpful in identifying patterns where numerous cases are studied. I use as illustration a research project on Latino grievances to offer a detailed explanation of the main steps in cluster analysis, providing specific considerations for its use with qualitative data. I specifically describe the issues of data transformation, the choice of clustering methods and similarity measures, the identification of a cluster solution, and the interpretation of the data in a qualitative context.
Keywords: Cluster Analysis, Qualitative Analysis, Data Exploration, Mixed