Case Studies Nested in Fuzzy-set QCA on Sufficiency: Formalizing Case Selection and Causal Inference
Abstract
Qualitative Comparative Analysis (QCA) is a method for cross-case analyses that works best when complemented with follow-up case studies focusing on the causal quality of the solution and its constitutive terms, the underlying causal mechanisms, and potentially omitted conditions. The anchorage of QCA in set theory demands criteria for follow-up case studies that are different from those known from regression-based multimethod research (MMR). Based on the evolving research on set-theoretic MMR, we introduce principles for formalized case selection and causal inference after a fuzzy-set QCA on sufficiency. Using an empirical example for illustration, we elaborate on the principles of counterfactuals for intelligible causal inference in the analysis of three different types of cases. Furthermore, we explain how case-based counterfactual inferences on the basis of QCA solutions are related to counterfactuals in the course of processing a truth table in order to produce a solution. We then flesh out two important functions that ideal types play for QCA-based case studies: First, they inform the development of formulas for the choice of the best available cases for with-case analysis and, second, establish the boundaries of generalization of the causal inferences.
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Sokol and Flash's ''Glass-box'' framework, designed specifically for decision trees, is argued to be easily extendable to capture the output of other logical (rule-based) models.
“Designed specifically for decision trees, their ''Glass-box'' frame- work is argued to be easily extendable to capture the output of other logical (rule-based) models.”
From A Survey of Contrastive and Counterfactual Explanation Generation Methods for Explainable Artificial Intelligence (2021) · cites this paper as [155]
Sokol and Flash rely on the Manhattan distance measuring leaf-to-leaf distance in the tree to retrieve the most relevant counterfactuals [46], [155].
“Alternatively, Sokol and Flash rely on the Manhattan distance measuring leaf-to-leaf distance in the tree to retrieve the most relevant counterfactuals [46], [155].”
From A Survey of Contrastive and Counterfactual Explanation Generation Methods for Explainable Artificial Intelligence (2021) · cites this paper as [155]
Interaction with users can be enhanced by means of voice-based explanations combined with textual explanations.
“Finally, interaction with users can be enhanced by means of voice-based explanations combined with textual explanations [46], [155].”
From A Survey of Contrastive and Counterfactual Explanation Generation Methods for Explainable Artificial Intelligence (2021) · cites this paper as [155]
As a majority of the considered frameworks are designed for tackling classification problems, counterfactual explanations operate on the notion of a contrast-class.
“As a majority of the considered frameworks are designed for tackling classification problems, contfactual explanations operate on the notion of a contrast-class (e.g., see [155]) answering the question: ''How is the prediction altered when the observation changes, given a classifier and an observation?''”
From A Survey of Contrastive and Counterfactual Explanation Generation Methods for Explainable Artificial Intelligence (2021) · cites this paper as [155]
An increasing number of interactive frameworks attempt not only to present the automatically generated explanations to the end-user but also interact with him or her.
“However, we find an increasing number of interactive frameworks that attempt not only to present the automatically generated explanations to the end-user but also interact with him or her [46], [150], [155].”
From A Survey of Contrastive and Counterfactual Explanation Generation Methods for Explainable Artificial Intelligence (2021) · cites this paper as [155]
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References 69 · Cited by 147
- Authors
- Schneider, C. Q., & Rohlfing, I.
- Affiliations
- Central European University - Budapest Campus (HU)
- University of Bremen (DE)
- Corresponding author
- Schneider, Carsten Q.
- Venue
- Sociological Methods & Research
- Publisher
- SAGE Publications
- Published
- 2014-05-26
- Volume
- 45
- Issue
- 3
- Pages
- 526-568
- ISSN
- 0049-1241 (ISSN-L)
- 1552-8294
- OpenAlex
- W1987013941
- Cited by
- 147
- References
- 69
- Citations by year
- 2026: 9 · 2025: 10 · 2024: 8 · 2023: 9 · 2022: 13 · 2021: 25 · 2020: 21 · 2019: 16 · 2018: 17 · 2017: 8 · 2016: 6 · 2015: 4 · 2014: 1
- FWCI
- 20.64
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Sociological Methods & Research (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Qualitative Comparative Analysis Research
- Social Sciences › Education › Qualitative Research Methods and Applications
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy and History of Science
- Keywords
- fuzzy-set QCA, sufficiency, case studies, case selection, counterfactual reasoning, causal inference, ideal types, truth tables, generalization, causal mechanisms
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