ERIC Number: EJ1137641
Record Type: Journal
Publication Date: 2017-Mar
Abstractor: As Provided
Reference Count: 7
Aggregation Bias and the Analysis of Necessary and Sufficient Conditions in fsQCA
Braumoeller, Bear F.
Sociological Methods & Research, v46 n2 p242-251 Mar 2017
Fuzzy-set qualitative comparative analysis (fsQCA) has become one of the most prominent methods in the social sciences for capturing causal complexity, especially for scholars with small- and medium-"N" data sets. This research note explores two key assumptions in fsQCA's methodology for testing for necessary and sufficient conditions--the cumulation assumption and the triangular data assumption--and argues that, in combination, they produce a form of aggregation bias that has not been recognized in the fsQCA literature. It also offers a straightforward test to help researchers answer the question of whether their findings are plausibly the result of aggregation bias.
Descriptors: Qualitative Research, Comparative Analysis, Social Science Research, Research Methodology, Test Bias, Test Reliability, Test Validity, Mathematical Models, Goodness of Fit
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Publication Type: Journal Articles; Reports - Evaluative
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