Full Description
A discussion of the case study method which develops an integrative framework for causal inference in small-n research. This framework is applied to research design tasks such as case selection and process tracing. The book presents the basics, state-of-the-art and arguments for improving the case study method and empirical small-n research.
Contents
Introduction Case, Case Study, and Causality: Core Concepts and Fundamentals Types of Case Study and Case Selection Forms and Problems of Comparisons Enhancing Causal Inference in Comparisons Process Tracing: Theory, Temporality, and Method From Evidence to Inference: Uses of Sources and Counterfactuals Frequentist and Bayesian Causal Inference in Tests of Hypotheses External Validity: Challenges and Strategies Conclusion: Guided by Theory, Moving Forward Step by Step
