Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Home
  • Home
Article
  • Cited by 3

  • Get access
    Add to cart USD25.00
    Check if you have access via personal or institutional login
    Log in Register

Causal modeling with multi-value and fuzzy-set Coincidence Analysis

  • Michael Baumgartner (a1) and Mathias Ambühl (a2)

Abstract

Coincidence Analysis (CNA) is a configurational comparative method of causal data analysis that is related to Qualitative Comparative Analysis (QCA) but, contrary to the latter, is custom-built for analyzing causal structures with multiple outcomes. So far, however, CNA has only been capable of processing dichotomous variables, which greatly limited its scope of applicability. This paper generalizes CNA for multi-value variables as well as continuous variables whose values are interpreted as membership scores in fuzzy sets. This generalization comes with a major adaptation of CNA’s algorithmic protocol, which, in an extended series of benchmark tests, is shown to give CNA an edge over QCA not only with respect to multi-outcome structures but also with respect to the analysis of non-ideal data stemming from single-outcome structures. The inferential power of multi-value and fuzzy-set CNA is made available to end users in the newest version of the R package cna.

Copyright

COPYRIGHT: © The European Political Science Association, 2018

Corresponding author

*Corresponding author. Email: michael.baumgartner@uib.no

References

Hide All
Ambühl, MBaumgartner, M (2018) ‘cna: Causal Modeling With Coincidence Analysis [Computer Program]. R Package Version 2.1.1’. Available at https://cran.r-project.org/package=cna accessed 26 September 2018.
Baumgartner, M (2009) Inferring Causal Complexity. Sociological Methods & Research 38, 71–101.
Baumgartner, M (2013) A Regularity Theoretic Approach to Actual Causation. Erkenntnis 78, 85–109.
Baumgartner, M (2015) Parsimony and Causality. Quality & Quantity 49, 839–856.
Baumgartner, MThiem, A (2017) ‘Often Trusted But Never (Properly) Tested: Evaluating Qualitative Comparative Analysis’. Sociological Methods & Research https://doi.org/10.1177/0049124117701487.
Baumgartner, MFalk, C (2018) ‘Boolean Difference-Making: A Modern Regularity Theory of Causation’. PhilSci Archive. Available at http://philsci-archive.pitt.edu/id/eprint/14876 accessed 26 September 2018.
Cronqvist, LBerg-Schlosser, D (2009) Multi-Value QCA (mvQCA). In Rihoux B and Ragin CC (eds), Configurational Comparative Methods: Qualitative Comparative Analysis (QCA) and Related Techniques, 69–86. London: Sage Publications.
Downing, BM (1992) The Military Revolution and Political Change: Origins of Democracy and Autocracy in Early Modern Europe. Princeton, NJ: Princeton University Press.
Duşa, A (2007) User Manual for the QCA(GUI) Package in R. Journal of Business Research 60(5), 576–586.
Goertz, G (2006) Social Science Concepts: A User’s Guide. Princeton, NJ: Princeton University Press.
Graßhoff, GMay, M (2001) Causal Regularities. In Spohn W, Ledwig M and Esfeld M (eds), Current Issues in Causation, 85–114. Paderborn: Mentis.
Hájek, P (1998) Metamathematics of Fuzzy Logic. Dordrecht: Kluwer.
Hume, D (1999 (1748)) An Enquiry Concerning Human Understanding. Oxford: Oxford University Press.
Lucas, SRSzatrowski, A (2014) Qualitative Comparative Analysis in Critical Perspective. Sociological Methodology 44(1), 1–79.
Mackie, JL (1974) The Cement of the Universe. A Study of Causation. Oxford: Clarendon Press.
Ragin, CC (1987) The Comparative Method. Berkeley, CA: University of California Press.
Ragin, CC (2006) Set Relations in Social Research: Evaluating their Consistency and Coverage. Political Analysis 14(3), 291–310.
Ragin, CC (2008) Redesigning Social Inquiry: Fuzzy Sets and Beyond. Chicago, IL: University of Chicago Press.
Ragin, CC (2009) Qualitative Comparative Analysis Using Fuzzy Sets (fsQCA). In Rihoux B and Ragin CC (eds), Configurational Comparative Methods: Qualitative Comparative Analysis (QCA) and Related Techniques, 87–121. Thousand Oaks, CA: Sage.
Suppes, P (1970) A Probabilistic Theory of Causality. Amsterdam: North Holland.
Thiem, A (2015) Using Qualitative Comparative Analysis for Identifying Causal Chains in Configurational Data: A Methodological Commentary on Baumgartner and Epple. Sociological Methods & Research 44(4), 723–736.
Thiem, A (2018) ‘QCApro: Advanced Functionality for Performing and Evaluating Qualitative Comparative Analysis [Computer Program]. R Package Version 1.1-2.’ Available at http://www.alrik-thiem.net/software/.

Related content

Powered by UNSILO
Type Description Title
PDF
Supplementary materials

Baumgartner and Ambühl supplementary material
Online Appendix

 PDF (202 KB)
202 KB
UNKNOWN
Supplementary materials

Baumgartner and Ambühl Dataset
Dataset

 Unknown
  • Cited by 3

  • Get access
    Add to cart USD25.00
    Check if you have access via personal or institutional login
    Log in Register

Causal modeling with multi-value and fuzzy-set Coincidence Analysis

  • Michael Baumgartner (a1) and Mathias Ambühl (a2)

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed.