The qualitative analysis of repertory grid data: Interpretive Clustering

This paper presents and illustrates Interpretive Clustering, an innovative and original method of qualitative analysis of Repertory Grid data. Repertory Grids are a popular and flexible method of research, but they have primarily been used to gather data that are analysed quantitatively. Although many researchers have used Grids more qualitatively, this is often limited to a content analysis of the elicited constructs across a sample of participants. Interpretive Clustering is a participant-led method which uses the grid data idiographically to explore how a participant's construing may 'cluster' around one or more issues. We show how this is quite different from a thematic analysis, and discuss how Interpretive Clustering can provide insights that are complementary to those gained from methods like thematic analysis. We conclude with suggestions for how this method, which we argue bridges the qualitative/quantitative divide, might be used in future research.