Ebook: Causal Case Study Methods: Foundations and Guidelines for Comparing, Matching, and Tracing
Author: Derek Beach Rasmus Brun Pedersen
- Tags: Methodology, Social Sciences, Politics & Social Sciences
- Year: 2016
- Publisher: University of Michigan Press
- Language: English
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In this comprehensive reconstruction of causal case study methods, Derek Beach, Rasmus Brun Pedersen, and their coauthors delineate the ontological and epistemological differences among these methods, offer suggestions for determining the appropriate methods for a given research project, and explain the step-by-step application of selected methods.
Causal Case Study Methods begins with the cohesive, logical foundations for small-n comparative methods, congruence methods, and process tracing, then delineate the distinctive types of causal relationships for which each method is appropriate. Next, the authors provide practical instruction for deploying each of the methods individually and in combination. They walk the researcher through each stage of the research process, starting with issues of concept formation and the formulation of causal claims in ways that are compatible with case-based research. They then develop guidelines for using Bayesian logic as a set of practical questions for translating empirical data into evidence that may or may not confirm causal inferences.
Widely acclaimed instructors, the authors draw upon their extensive experience at the graduate level in university classrooms, summer and winter school courses, and professional workshops, around the globe.
Causal Case Study Methods begins with the cohesive, logical foundations for small-n comparative methods, congruence methods, and process tracing, then delineate the distinctive types of causal relationships for which each method is appropriate. Next, the authors provide practical instruction for deploying each of the methods individually and in combination. They walk the researcher through each stage of the research process, starting with issues of concept formation and the formulation of causal claims in ways that are compatible with case-based research. They then develop guidelines for using Bayesian logic as a set of practical questions for translating empirical data into evidence that may or may not confirm causal inferences.
Widely acclaimed instructors, the authors draw upon their extensive experience at the graduate level in university classrooms, summer and winter school courses, and professional workshops, around the globe.
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