Comparative Case Study Research Method

Comparative Case Study Research Method-11
We further elaborate on the distinction between causal effects and causal mechanisms and their role in causal inference and case studies.In addition, a thorough treatment of causal inference requires a consideration of different notions of causal effects.

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Since there is a menu of types and case selection strategies and both are linked to different modes of causal inference (see day 2), we spend two days on these topics.

The second week starts on day 6 with a session on the , including a consideration of John Stuart Mill’s (in)famous method of difference and method of agreement.

Second, “lab sessions” give the participants the opportunity to apply the new insights to their own project; this is achieved by discussions about the participants’ projects in small groups and among the entire class.

Third, the assignment portion involves in-class discussions of short assignments (simple methodological questions) related to the participants studies and published case studies from different fields within political science.

A distinction is made between correlations (e.g., the more X, the more Y) and set-relations (e.g., if X, then Y) as these currently represent the two major perspectives on causal effects in the social sciences.

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Finally, we introduce the basics of , as it became increasingly important in the recent literature about case studies and process tracing.

is Professor of Methods of Comparative Political Research at the Cologne Center for Comparative Politics, University of Cologne.

He researches social science methods with a focus on qualitative methods (case studies and process tracing), Qualitative Comparative Analysis and multimethod research.

First, the can be the cross-case level (often understood as the macro level), or the within-case level (i.e. Third, we introduce the importance of difference-making and counterfactuals for causal inference and elaborate the difference between and when and how we claim that an observed empirical association reflects a causal relationship.

We introduce the the criterion of difference-making as the benchmark for inferring causal relationships.

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