‘Membership matters’: applying Membership Categorisation Analysis (MCA) to qualitative data using Computer‐Assisted Qualitative Data Analysis (CAQDAS) Software

Abstract

This paper introduces and outlines a methodology that may be unfamiliar to some qualitative researchers: Membership Categorisation Analysis (MCA). The first section of the paper explains the basic principles of MCA and why it is a valid method for exploring the power of categorisations in texts and talk. Additionally, it explains why MCA differs from other forms of qualitative data analysis. The second section begins with a discussion of why researchers might or might not use Computer‐Assisted Qualitative Data Analysis (CAQDAS) Software. Subsequently, a detailed description of how MCA was applied to qualitative data using the CAQDAS software package NVivo is outlined. To provide examples, this paper draws on a project that used MCA to analyse the interview accounts of 25 young people who had taken a Gap Year between leaving school and beginning university. The paper concludes that qualitative researchers should consider using MCA and that CAQDAS is a useful tool to aid its application.