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A review of integrated QCA and statistical analyses

Author

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  • Johannes Meuer

    (ETH Zurich)

  • Christian Rupietta

    (University of Wuppertal
    University of Zurich)

Abstract

Systematically combining quantitative and qualitative research approaches offers the potential for a more comprehensive and nuanced understanding of social scientific phenomena. With their strong opportunities for building, qualifying, and testing social scientific theories, methodological integrations thus enable researchers to make substantive contributions that would not have been possible with one method alone. In this article we demonstrate how the integration of Qualitative Comparative Analysis (QCA) and conventional statistical analysis offers researchers new opportunities for contributing to the social sciences. Whereas statistical analysis is variable-oriented and relies on correlational analysis to make comparisons across cases, QCA is based on set theory, is case oriented, and relies on Boolean algebra to make comparisons between cases. Drawing on the literature on the interdependency between theoretical contribution and methodology, we review studies that integrate QCA and statistical analysis to explain how the specific combination of these two approaches allows researchers to strengthen the theoretical contribution of their research. From our review we identify common challenges and provide solutions for integrating QCA and statistical analysis.

Suggested Citation

  • Johannes Meuer & Christian Rupietta, 2017. "A review of integrated QCA and statistical analyses," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(5), pages 2063-2083, September.
    • Handle: RePEc:spr:qualqt:v:51:y:2017:i:5:d:10.1007_s11135-016-0397-z
    DOI: 10.1007/s11135-016-0397-z
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    References listed on IDEAS

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