Analysing necessity and sufficiency with Qualitative Comparative Analysis: how do results vary as case weights change?

Analysing necessity and sufficiency with Qualitative Comparative Analysis: how do results vary as... Ragin’s Qualitative Comparative Analysis (QCA) and related set theoretic methods are increasingly popular. This is a welcome development, since it encourages systematic configurational analyses of social phenomena. One downside of this growth in popularity is a tendency for more researchers to use the approach in a formulaic manner—something made possible, and more likely, by the availability of free software. We wish to see QCA employed, as Ragin intended, in a self-critical manner. For this to happen, researchers need to understand more of what is going on behind the results generated by the available software packages. One important aspect of set theoretic analyses of sufficiency and necessity is the effect that the distribution of cases in a dataset can have on results. We explore this issue in a number of ways. We begin by exploring how both deterministic and nondeterministic data-generating processes are reflected in the analyses of populations differing in only the weights of types of cases. We show how and why weights matter in causal analyses that focus on necessity and also, where models are not fully specified, sufficiency. We then draw on this discussion to show that a recent textbook discussion of hidden necessary conditions is weakened as a result of its neglect of weighting issues. Finally, having shown that case weights raise a number of difficulties for set theoretic analyses, we offer suggestions, drawing on two imagined population datasets concerning health outcomes, for mitigating their effect. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

Analysing necessity and sufficiency with Qualitative Comparative Analysis: how do results vary as case weights change?

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Publisher
Springer Netherlands
Copyright
Copyright © 2015 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/s11135-014-0151-3
Publisher site
See Article on Publisher Site

Abstract

Ragin’s Qualitative Comparative Analysis (QCA) and related set theoretic methods are increasingly popular. This is a welcome development, since it encourages systematic configurational analyses of social phenomena. One downside of this growth in popularity is a tendency for more researchers to use the approach in a formulaic manner—something made possible, and more likely, by the availability of free software. We wish to see QCA employed, as Ragin intended, in a self-critical manner. For this to happen, researchers need to understand more of what is going on behind the results generated by the available software packages. One important aspect of set theoretic analyses of sufficiency and necessity is the effect that the distribution of cases in a dataset can have on results. We explore this issue in a number of ways. We begin by exploring how both deterministic and nondeterministic data-generating processes are reflected in the analyses of populations differing in only the weights of types of cases. We show how and why weights matter in causal analyses that focus on necessity and also, where models are not fully specified, sufficiency. We then draw on this discussion to show that a recent textbook discussion of hidden necessary conditions is weakened as a result of its neglect of weighting issues. Finally, having shown that case weights raise a number of difficulties for set theoretic analyses, we offer suggestions, drawing on two imagined population datasets concerning health outcomes, for mitigating their effect.

Journal

Quality & QuantitySpringer Journals

Published: Jan 13, 2015

References

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