Multivariate data analysis of categorical data: taking advantage of the rhetorical power of numbers in qualitative research

Omar Sacilotto Donaires (), Luciana Oranges Cezarino (), Lara Bartocci Liboni (), Evandro Marcos Saidel Ribeiro () and Flávio Pinheiro Martins ()
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Omar Sacilotto Donaires: University of São Paulo
Luciana Oranges Cezarino: Ca’ Foscari University of Venice
Lara Bartocci Liboni: University of São Paulo
Evandro Marcos Saidel Ribeiro: University of São Paulo
Flávio Pinheiro Martins: University College London

Quality & Quantity: International Journal of Methodology, 2023, vol. 57, issue 6, No 17, 5283-5312

Abstract: Abstract There is a general understanding that quantitative methods are more trustworthy than methods based uniquely on words and discourse. In this paper, we depart from this thinking to explore how numbers can be used in qualitative research so as to take advantage of its expressive power. We present a technique that enables the application of multivariate data analysis—particularly of interdependence methods, which include principal components analysis, factor analysis, cluster analysis, and multidimensional scaling—in qualitative research. The technique consists in translating categorical data from qualitative research into a binary form that enables the calculation of correlations, similarity coefficients, and distances, thus enabling the application of the interdependence methods of multivariate data analysis. Results also include a brief taxonomy of literature review. It contributes by demonstrating how qualitative research can benefit from quantitative analysis.

Keywords: Qualitative research; Quantitative analysis; Literature review; Bibliometrics; Multivariate data analysis; Qualitative synthesis (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11135-022-01589-1

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