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Testing for Necessary and/or Sufficient Causation: Which Cases Are Relevant?

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  • Seawright, Jason

Abstract

Previous researchers have argued that necessary and/or sufficient causes should be tested through research designs that consider only cases with limited combinations of scores on the independent and the dependent variables. I explore the utility for causal inference of the design proposed by these authors, as compared to an “All Cases Design.” I find that, if researchers define the population carefully and appropriately, each case in the population contributes to causal inference and is therefore useful. Previous authors reject this claim on the basis of a view that holds constant the marginal distribution of either the dependent or the independent variable across the working and the alternate hypotheses. I argue that this restriction is not generally appropriate, and hence, an analysis that samples from the entire population is logically defensible. I also argue that this design is more statistically efficient. A reanalysis of two well-known studies demonstrates that sampling from all cases in the relevant population produces greater confidence in the hypothesis than sampling only from cases that experience the outcome.

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  • Seawright, Jason, 2002. "Testing for Necessary and/or Sufficient Causation: Which Cases Are Relevant?," Political Analysis, Cambridge University Press, vol. 10(2), pages 178-193, April.
  • Handle: RePEc:cup:polals:v:10:y:2002:i:02:p:178-193_00
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    Cited by:

    1. Eva Thomann & Martino Maggetti, 2020. "Designing Research With Qualitative Comparative Analysis (QCA): Approaches, Challenges, and Tools," Sociological Methods & Research, , vol. 49(2), pages 356-386, May.
    2. Derek Beach & Rasmus Brun Pedersen, 2018. "Selecting Appropriate Cases When Tracing Causal Mechanisms," Sociological Methods & Research, , vol. 47(4), pages 837-871, November.
    3. De Souter Luna, 2024. "Evaluating Boolean relationships in Configurational Comparative Methods," Journal of Causal Inference, De Gruyter, vol. 12(1), pages 1-25, January.
    4. Jack S. Levy, 2008. "Case Studies: Types, Designs, and Logics of Inference," Conflict Management and Peace Science, Peace Science Society (International), vol. 25(1), pages 1-18, February.
    5. Aaron Katz & Matthias vom Hau & James Mahoney, 2005. "Explaining the Great Reversal in Spanish America," Sociological Methods & Research, , vol. 33(4), pages 539-573, May.

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