Quality & Quantity

, Volume 50, Issue 1, pp 121–128 | Cite as

Analyzing multilevel data with QCA: yet another straightforward procedure

  • Alrik ThiemEmail author


A significant body of social-scientific literature has developed contextual theories. In a recent contribution to Quality & Quantity, Denk and Lehtinen (Qual Quant 48(6):3475–3487, 2014) present Comparative Multilevel Analysis (CMA) as an innovative method whereby the effects of contexts on outcomes of interest can be studied configurationally if combined with Qualitative Comparative Analysis (QCA). In contradistinction, I argue that CMA is neither innovative in nor necessary for ascertaining the influence of context in a configurational-comparative manner. QCA is appreciably more powerful than the authors acknowledge and provides all required functionality. In repetition of Rohlfing’s (Int J Soc Res Methodol 15(6):497–506, 2012) verdict on Denk’s (Int J Soc Res Methodol 13(1):29–39, 2010) earlier version of CMA, I conclude that QCA need not be extended in the direction proposed by Denk and Lehtinen. Researchers interested in the contextual analysis of configurational data are well-served by the existing toolbox of QCA.


Comparative Multilevel Analysis Configurational comparative methods Contextual analysis csQCA fsQCA  mvQCA QCA Qualitative Comparative Analysis 

Supplementary material

11135_2014_140_MOESM1_ESM.txt (3 kb)
Supplementary material 1 (txt 3 KB)


  1. Baumgartner, M.: Parsimony and causality. Qual. Quant. (2014). doi: 10.1007/s11.135-014-0026-7
  2. Berg-Schlosser, D., Cronqvist, L.: Macro-quantitative vs. macro-qualitative methods in the social sciences—an example from empirical democratic theory employing new software. Hist. Soc. Res. 30(4), 154–175 (2005)Google Scholar
  3. Canes-Wrone, B., Shotts, K.W.: The conditional nature of presidential responsiveness to public opinion. Am. J. Polit. Sci. 48(4), 690–706 (2004)CrossRefGoogle Scholar
  4. Cronqvist, L.: Presentation of Tosmana: adding multi-valued variables and visual aids to QCA. COMPASSS Working Paper 2004–20, (2004). Accessed 5 May 2014
  5. Cronqvist, L., Berg-Schlosser, D.: Multi-value QCA (mvQCA). In: Rihoux, B., Ragin, C.C. (eds.) Configurational Comparative Methods: Qualitative Comparative Analysis (QCA) and Related Techniques, pp. 69–86. Sage Publications, London (2009)CrossRefGoogle Scholar
  6. Denk, T.: Comparative multilevel analysis: proposal for a methodology. Int. J. Soc. Res. Methodol. 13(1), 29–39 (2010)CrossRefGoogle Scholar
  7. Denk, T., Lehtinen, S.: Contextual analyses with QCA-methods. Qual. Quant. 48(6), 3475–3487 (2014)CrossRefGoogle Scholar
  8. Duşa, A., Thiem, A.: QCA: a package for Qualitative Comparative Analysis, R Package Version 1.1–3. (2014)
  9. Nincic, M.: U.S. Soviet policy and the electoral connection. World Polit. 42(3), 370–396 (1990)CrossRefGoogle Scholar
  10. R Development Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna (2014)Google Scholar
  11. Ragin, C.C.: The Comparative Method: Moving Beyond Qualitative and Quantitative Strategies. University of California Press, Berkeley (1987)Google Scholar
  12. Ragin, C.C.: Set relations in social research: evaluating their consistency and coverage. Polit. Anal. 14(3), 291–310 (2006)CrossRefGoogle Scholar
  13. Ragin, C.C., Sonnett, J.: Between complexity and parsimony: limited diversity, counterfactual cases and comparative analysis. In: Kropp, S., Minkenberg, M. (eds.) Vergleichen in der Politikwissenschaft, pp. 180–197. VS Verlag für Sozialwissenschaften, Wiesbaden (2005)Google Scholar
  14. Ragin, C.C., Mayer, S.E., Drass, K.A.: Assessing discrimination: a Boolean approach. Am. Sociol. Rev. 49(2), 221–234 (1984)Google Scholar
  15. Rohlfing, I.: Analyzing multilevel data with QCA: a straightforward procedure. Int. J. Soc. Res. Methodol. 15(6), 497–506 (2012)CrossRefGoogle Scholar
  16. Thiem, A.: Clearly crisp, and not fuzzy: a reassessment of the (putative) pitfalls of multi-value QCA. Field Methods 25(2), 197–207 (2013)CrossRefGoogle Scholar
  17. Thiem, A.: Parameters of fit and intermediate solutions in multi-value Qualitative Comparative Analysis. Qual. Quant. doi: 10.1007/s11.135-014-0015-x (2014a)
  18. Thiem, A.: Unifying configurational comparative methods: generalized-set Qualitative Comparative Analysis. Sociol. Methods Res. 43(2), 313–337 (2014b)Google Scholar
  19. Thiem, A.: Navigating the complexities of Qualitative Comparative Analysis: case numbers, necessity relations and model ambiguities. Eval. Rev. doi: 10.1177/0193841X14550863 (2014c)
  20. Thiem, A., Duşa, A.: Boolean minimization in social science research: a review of current software for Qualitative Comparative Analysis (QCA). Soc. Sci. Comput. Rev. 31(4), 505–521 (2013a)Google Scholar
  21. Thiem, A., Duşa, A.: QCA: a package for Qualitative Comparative Analysis. R J. 5(1), 87–97 (2013b)Google Scholar
  22. Thiem, A., Duşa, A.: Qualitative Comparative Analysis with R: A User’s Guide. Springer, New York (2013c)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Department of PhilosophyUniversity of GenevaGenevaSwitzerland

Personalised recommendations