Multi-Method Social Science. (eBook, 2016) [WorldCat.org]
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Multi-Method Social Science.
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Multi-Method Social Science.

Author: Jason Seawright
Publisher: Cambridge : Cambridge University Press, 2016.
Series: Strategies for social inquiry.
Edition/Format:   eBook : Document : English
Summary:

Reflecting the rising popularity of research that combines qualitative and quantitative social science, this book provides the first systematic guide to designing multi-method research. It considers  Read more...

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Genre/Form: Electronic books
Additional Physical Format: Print version:
Seawright, Jason.
Multi-Method Social Science.
Cambridge : Cambridge University Press, ©2016
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Jason Seawright
ISBN: 9781316160831 1316160831
OCLC Number: 963666324
Description: 1 online resource (248 pages)
Contents: Cover; Half-title; Series page; Title page; Copyright information; Table of contents; List of figures and tables; Acknowledgments; 1 Integrative Multi-Method Research; 1.1 The Multi-Method Boom; 1.2 Integration, not Triangulation; 1.3 The Origins of Proportional Representation: An Integrative Example; 1.4 Overview of the Book; Notes; 2 Causation as a Shared Standard; 2.1 The Potential-Outcomes Framework; 2.2 Regression and Causal Inference; 2.3 Regression and the Potential-Outcomes Framework; 2.4 Conclusions; Notes; 3 Using Case Studies to Test and Refine Regressions. 3.1 Identifying a Case's Causal Counterfactuals3.2 Validating Measurement; 3.3 Testing or Discovering Hypotheses about Causal Pathways; 3.4 Searching for Confounders; 3.5 Refining Regressions to Incorporate Qualitative Insights; Notes; 4 Case Selection after Regression; 4.1 Case Selection Techniques: A Brief Overview; 4.1.1 Major Goals of Case-Study Research; 4.1.2 Techniques for Choosing Cases; 4.2 Why Deviant and Extreme-on-the-Independent-Variable ... ; 4.2.1 Deviant Cases; 4.2.2 Extreme Cases; 4.2.3 Random Sampling; 4.2.4 Typical Cases; 4.2.5 Influential Cases. 4.2.6 Most Similar, Most Different, and Contrast Cases4.2.7 Pathway Cases; 4.2.8 Conclusions; 4.3 The Fit Between Techniques and Goals: Simulations; 4.4 Conclusions; Notes; 5 Combining Case Studies and Matching; 5.1 Finding Omitted Variables; 5.2 Checking for Measurement Problems; 5.3 Causal Pathways; 5.4 Conclusions; Notes; 6 Combining Case Studies and Natural Experiments; 6.1 True Natural Experiments; 6.2 Regression-Discontinuity Designs; 6.3 Instrumental Variables Natural Experiments; 6.4 Conclusions; Notes; 7 Embedding Case Studies within Experiments. 7.1 Experiments and the Potential-Outcomes Framework7.2 Case Studies and Experiments: Basic Considerations; 7.3 Old Issues: Measurement and Causal Pathways; 7.4 Testing SUTVA; 7.5 Experimental Realism and External Validity; 7.6 Conclusions; Notes; 8 Multi-Method Case Studies; 8.1 Testing Generalizability; 8.2 Quantifying Effect Sizes; 8.3 Quantitative Analysis as a Step in Process Tracing; 8.4 Quantitative Causal Effect Estimates as the Outcomes to be Explained; 8.5 Multi-Method Research with Other Modes of Qualitative Research; 8.6 Conclusions; Notes. Appendix: Qualitative Causal Models andthe Potential-Outcomes Framework1.1 Necessary and/or Sufficient Causes; 1.2 INUS and SUIN Causes; 1.3 Path-Dependent and Critical-Juncture Causal Models; 1.4 Causal Mechanisms and Pathways; 1.5 Other Causal Categories; 1.6 The Effects-of-Causes versus Causes-of-Effects Distinction; References; Index.
Series Title: Strategies for social inquiry.

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