Titlebook: Case Studies and Causal Inference; An Integrative Frame Ingo Rohlfing Book 2012 Palgrave Macmillan, a division of Macmillan Publishers Limi

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Divisions of labour and hierarchy and means to address them pertain to case studies that build hypothesis, test them, or seek to modify them in order to make sense of puzzling cases. A separate and important topic reserved for this chapter concerns frequentist and Bayesian causal inference as two ways of producing inferences in tes

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Thomas Hardy: A Partial Portrait (1996),e to those cases that are part of the population and have not been analyzed.. In qualitative case studies, one generalizes inferences about causal effects and causal mechanisms because a regularities perspective implies the assumption that both are regular (Kühn and Rohlfing 2010). The small-n liter

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2947-5201 plied 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.978-1-349-31657-1978-1-137-27132-7Series ISSN 2947-5201 Series E-ISSN 2947-521X

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ECPR Research Methodshttp://image.papertrans.cn/c/image/222239.jpg

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Politics, Careers and Elections,ally demonstrates that distinguishing between the three dimensions introduced in Chapter 1 – research goals, levels of analysis, and variants of causal effects – is central for case studies and case selection.

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Frequentist and Bayesian Causal Inference in Tests of Hypotheses,llecting individual observations as opposed to their number. Among other things, a discussion of these two modes of causal inferences closes the circle with respect to Chapter 3. As is detailed below, distribution-based case selection is integral to frequentist causal inference, whereas Bayesianismrelies on the theory-based choice of cases.

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