Multi-Resolution Design: Using Qualitative and Quantitative Analyses to Recursively Zoom in and out of the Same Dataset
A recent challenge is how to mix qualitative interpretation with computational techniques to analyze big qualitative data. To this end, we propose “multi-resolution design” for mixed method analysis of the same data : qualitative analysis zooms-in to provide in-depth contextual insight and quantitative analysis zooms-out to provide measures, associations, and statistical models. The raw qualitative data is transformed between excerpts, counts, and measures; with each having unique gains and losses. Multi-resolution designs entail transforming the data back-and-forth between these data types, recursively quantitizing and qualitizing the data. Two empirical studies illustrate how multi-resolution design can support abductive inference and increase validity. This contributes to mixed methods literature a conceptualization of how mixed analysis of the same big qualitative dataset can create tightly integrated synergies.
Authors
- Marcos José Bernal Marcos (ORCID: https://orcid.org/0000-0003-0529-9198)
- Tania Zittoun (ORCID: https://orcid.org/0000-0003-3203-2819)
- Alex Gillespie (ORCID: https://orcid.org/0000-0002-0162-1269)
- Vlad Petre Glăveanu (ORCID: https://orcid.org/0000-0002-6029-6718)
- Constance de Saint Laurent (ORCID: https://orcid.org/0000-0003-2074-1765)
Institutions
- National University of Ireland, Maynooth (IE)
- National University of Ireland (IE)
- Universidad Loyola Andalucía (ES)
- Dublin City University (IE)
- University of Neuchâtel (CH)
- London School of Economics and Political Science (GB)
Publication Details
- Journal
- Journal of Mixed Methods Research
- Published
- 2024-09-16
- DOI
- https://doi.org/10.1177/15586898241284696
- Citations
- 9
- Primary Topic
- Qualitative Comparative Analysis Research
- Type
- article
- Field-Weighted Citation Impact
- 7.92
Funders
- Goddard Space Flight Center