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ACCORds: Advancing Configurational Comparative Research Methods

Project Period: 09/17 - 08/2023

Funding Volume: 2'097'000 Swiss Francs

Principal Investigator: Alrik Thiem (University of Lucerne)

Collaborators: Lusine Mkrtchyan (post-doc), Zuzana Sebechlebská (programmer)

Albeit often regarded as mere means to achieve other ends, research methods are central to the advance of all sciences. Against this backdrop, the field of empirical social research methods has witnessed a major revolution over the last two decades: the appearance of a new group of techniques known today as Configurational Comparative Methods (CCMs; Rihoux and Ragin 2009). Mill's methods of agreement and difference (Mill 1843/1973:388-396), the four variants of Qualitative Comparative Analysis (QCA), namely crisp-set QCA (csQCA; Ragin 1987), fuzzy-set QCA (fsQCA; Ragin 2000; 2008), multi-value QCA (mvQCA; Cronqvist and Berg-Schlosser 2009), and generalized-set QCA (gsQCA; Thiem 2014), Coincidence Analysis (CNA; Baumgartner 2009) and Event Structure Analysis (Heise 1989) can all be considered members of this family. The most recent family member, which also represents the analytically most powerful CCM so far, is Combinational Regularity Analysis (CORA; Thiem, Mkrtchyan and Sebechlebská, 2022).

As the largest part of the potential of these methods remains unrealized, ACCORds will take CCMs a quantum leap forward. The project will have three dimensions. First, the functional dimension subsumes all topics related to technical advances in the capabilities of CCMs, including configurational big data analysis and algorithmic optimization, sequential complex cause structures, sensitivity diagnostics, and longitudinal data structures; second, the epistemological dimension groups together all topics dealing with broader methodological questions in relation to configurational research, including methodological property evaluation and configurational mixed-method research; and third, the purpose of the computational dimension is to provide a set of tools for testing and verifying the advances achieved under the first dimension, and to make them accessible to the scientific community in the form of a powerful software package. To optimize its scientific output and impact, ACCORds also seeks ad hoc collaborations with applied researchers from disciplines where CCMs have already been employed, such as political science and sociology, as well as from disciplines where these methods have not yet been introduced, such as psychology. 

In summary, ACCORds represents the first major effort to draw all current strands of CCM research together in a single, focused project whose overriding objective it is to take the field of configurational data analysis to the next distinct stage of development.



Baumgartner, M. (2009). Inferring causal complexity. Sociological Methods & Research 38(1), 71-101.

Cronqvist, L., & Berg-Schlosser, D. (2009). Multi-value QCA (mvQCA). In B. Rihoux & C. C. Ragin (Eds.), Configurational Comparative Methods: Qualitative Comparative Analysis (QCA) and related techniques (pp. 69-86). London: Sage Publications.

Heise, D. R. (1989). Modeling event structures. Journal of Mathematical Sociology 14(2-3), 139-169.

Mill, J. S. [edited by J. M. Robson]. (2006, 1973, [1843]). A system of logic, ratiocinative and inductive: Being a connected view of the principles of evidence and the methods of scientific investigation. Toronto: University of Toronto Press.

Ragin, C. C. (1987). The comparative method: Moving beyond qualitative and quantitative strategies. Berkeley: University of California Press.

—. (2000). Fuzzy-set social science. Chicago: University of Chicago Press.

—. (2008). Redesigning social inquiry: Fuzzy sets and beyond. Chicago: University of Chicago Press.

Rihoux, B., & Ragin, C. C. (Eds.). (2009). Configurational Comparative Methods: Qualitative Comparative Analysis (QCA) and related techniques. London: SAGE.

Thiem, A. (2014). Unifying Configurational Comparative Methods: Generalized-set Qualitative Comparative Analysis. Sociological Methods & Research 43(2), 313-337.

Thiem, A., Mkrtchyan, L. & Sebechlebská, Z. (2022). Combinational Regularity Analysis (CORA) - A New Method for Uncovering Complex Causation in Medical and Health Research. BMC Medical Research Methodology.