期刊
SOCIOLOGICAL METHODS & RESEARCH
卷 51, 期 3, 页码 1211-1243出版社
SAGE PUBLICATIONS INC
DOI: 10.1177/0049124120914955
关键词
qualitative comparative analysis (QCA); large-N; robustness; validity; causality; critical realism
This article connects QCA's substantive-interpretation approach of causality to critical realism and validates the validity of causal claims in large-N QCA studies through robustness tests.
Applying qualitative comparative analysis (QCA) to large Ns relaxes researchers' case-based knowledge. This is problematic because causality in QCA is inferred from a dialogue between empirical, theoretical, and case-based knowledge. The lack of case-based knowledge may be remedied by various robustness tests. However, being a case-based method, QCA is designed to be sensitive to such tests, meaning that also large-N QCA robustness tests must be evaluated against substantive knowledge. This article connects QCA's substantive-interpretation approach of causality to critical realism. From that perspective, it identifies relevant robustness tests and applies them to a real-data large-N QCA study. Robustness test findings are visualized in a robustness table, and this article develops criteria to substantively interpret them. The robustness table is introduced as a tool to substantiate the validity of causal claims in large-N QCA studies.
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