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1 results

  • 4 - Drawing Contingent Generalizations from Case Studies

  • from Part I - Internal and External Validity Issues in Case Study Research
  • Edited by Jennifer Widner, Princeton University, New Jersey, Michael Woolcock, Daniel Ortega Nieto
  • Book:
    The Case for Case Studies
    Published online:
    05 May 2022
    Print publication:
    26 May 2022, pp 62-86
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  • Summary

    Andrew Bennett help us think about what steps are necessary to use case studies to identify causal relationships and draw contingent generalizations. He suggests that case study research employs Bayesian logic rather than frequentist logic. “Bayesian logic treats probabilities as degrees of belief in alternative explanations, and it updates initial degrees of belief (called ‘priors’) by using assessments of the probative value of new evidence vis-à-vis alternative explanations (the updated degree of belief is known as the ‘posterior’).” Bennett sketches four approaches: generalization from ‘typical’ cases, generalization from most- or least-likely cases, mechanism-based generalization, and typological theorizing, with special attention to the last two. The study of deviant, or outlier, cases and cases that have high values on the independent variable of interest (theory of change) may prove helpful, Bennett suggests, aiding the identification of scope conditions, new explanations, and omitted variables.