Abstract
This paper addresses an issue that so far has received relatively little attention in methodological discussions about Qualitative Comparative Analysis (QCA), namely the challenges researchers face when using qualitative data in QCA analyses. Building on a literature review of 22 empirical studies using qualitative data for QCA, we discuss the challenges and ways to address these: (1) Which qualitative data to use? (2) How to determine the thresholds for in- and exclusion of a set? (3) How to establish the degree to which a case is ‘in’ or ‘out’ of a set? (4) How to differentiate between those concepts that are truly absent and those that are not mentioned? (5) Which sensitivity tests to conduct for assessing the robustness of the findings based on qualitative data? (6) How to present the calibration process transparently (and concisely)? By discussing these challenges using especially current practices in QCA-studies that are mostly informed by qualitative data, we aim to contribute to the best practices in QCA research.
| Original language | English |
|---|---|
| Publication status | Published - 2 Jun 2017 |
Publication series
| Name | COMPASSS Working Paper Series |
|---|---|
| No. | 2017-88 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 10 Reduced Inequalities
Keywords
- Qualitative Comparative Analysis
- Qualitative data
- Calibration
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