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Contextual analyses with QCA-methods

Abstract

Contextual analyses are essential in comparative research, as they investigate the importance of contextual conditions for causal relationships. During the last decades, an increasing number of comparative studies have also focused on how contextual conditions affect causal relationships. At the same time, new comparative methods have been developed based on set-theoretical logics. Two of the most prominent methods are csQCA and fsQCA, which are used in comparative studies with increasing frequency. However, the conventional design for contextual analysis is still based on quantitative methods and the use of interaction-factors. This article discusses why the use of interaction-factors is not suitable together with QCA-methods. Instead of the conventional design, the article presents an alternative design for contextual analyses with QCA-methods grounded on subgroup-design. Based on one recently-developed methodology comparative multilevel analysis (CMA), some guidelines for performing contextual analyses with two set-theoretical methods (csQCA and fsQCA) are presented. As illustrated with examples, the combination of CMA and QCA provides opportunities to use QCA for contextual analysis.

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Fig. 1

Notes

  1. 1.

    Positive conditionally means that the presence of contextual condition is necessary for the existence of causal relationship, while negative conditionally refers to when the presence of contextual condition dissolves the causal relationship.

  2. 2.

    In the following examples (Tables 3, 4), coefficients for consistency and coverage are used. However, fsQCA offers additional coefficients that indicate theoretical set-relationships and can be used in contextual analyses with CMA. For example, when combinations of conditions are analyzed, different aspects of theoretical set-relationships are indicated by solution consistency, solution coverage, raw coverage, and unique coverage (Ragin 2008; Schneider and Wagemann 2012). These coefficients, in combination with CMA, provide opportunities to analyze how context affects different aspects of causal relationships.

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Correspondence to Thomas Denk.

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Denk, T., Lehtinen, S. Contextual analyses with QCA-methods. Qual Quant 48, 3475–3487 (2014). https://doi.org/10.1007/s11135-013-9968-4

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Keywords

  • Contextual analysis
  • QCA
  • Comparative multilevel analysis
  • Fuzzy-set
  • Interaction