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Guarding Against False Positives in Qualitative Comparative Analysis

Published online by Cambridge University Press:  04 January 2017

Bear F. Braumoeller
Bear F. Braumoeller*
Affiliation:
Department of Political Science, The Ohio State University, Columbus, OH 43210
*
e-mail: [email protected] (corresponding author)
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Abstract

The various methodological techniques that fall under the umbrella description of qualitative comparative analysis (QCA) are increasingly popular for modeling causal complexity and necessary or sufficient conditions in medium-N settings. Because QCA methods are not designed as statistical techniques, however, there is no way to assess the probability that the patterns they uncover are the result of chance. Moreover, the implications of the multiple hypothesis tests inherent in these techniques for the false positive rate of the results are not widely understood. This article fills both gaps by tailoring a simple permutation test to the needs of QCA users and adjusting the Type I error rate of the test to take into account the multiple hypothesis tests inherent in QCA. An empirical application–a reexamination of a study of protest-movement success in the Arab Spring–highlights the need for such a test by showing that even very strong QCA results may plausibly be the result of chance.

Type
Articles
Information
Political Analysis , Volume 23 , Issue 4 , Autumn 2015 , pp. 471 - 487
Copyright
Copyright © The Author 2015. Published by Oxford University Press on behalf of the Society for Political Methodology 

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Footnotes

Author's note: Thanks to Christopher Achen, David Collier, Jirka Lewandowski, the scholars who attended the 2014 summer seminars on Boolean logit at WZB Berlin, and those who attended my sessions at the 2014 IQMR Summer Institute in Syracuse, New York, for valuable feedback, and to Andrew Rosenberg and Austin Knuppe for invaluable research assistance. Replication Data are available on the Dataverse site for this article, http://dx.doi.org/10.7910/DVN/GY6P9I.

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