Analyzing multilevel data with QCA: yet another straightforward procedure

Analyzing multilevel data with QCA: yet another straightforward procedure 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

Analyzing multilevel data with QCA: yet another straightforward procedure

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Publisher
Springer Netherlands
Copyright
Copyright © 2014 by Springer Science+Business Media Dordrecht
Subject
Social Sciences; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1007/s11135-014-0140-6
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

Quality & QuantitySpringer Journals

Published: Dec 5, 2014

References

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