This book provides the first systematic guide to designing multi-method research, considering a wide range of statistical and qualitative tools.
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Jason Seawright is an Associate Professor in the Department of Political Science at Northwestern University. He has written extensively about multi-method research and has published in journals including Political Analysis, Political Research Quarterly, Sociological Methodology, and Sociological Methods and Research. He was the author or co-author of several chapters in Rethinking Social Inquiry: Diverse Tools, Shared Standards, edited by Henry E. Brady and David Collier. He has taught courses on multi-method research design at institutes worldwide.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Hardcover. Etat : new. Hardcover. Reflecting the rising popularity of research that combines qualitative and quantitative social science, Multi-Method Social Science provides the first systematic guide to designing multi-method research. It argues that methods can be productively combined using the framework of integrative multi-method research, with one method used to carry out a final causal inference, and methods from other traditions used to test the key assumptions involved in that causal inference. In making this argument, Jason Seawright considers a wide range of statistical tools including regression, matching, and natural experiments. The book also discusses qualitative tools including process tracing, the use of causal process observations, and comparative case study research. Along the way, the text develops over a dozen multi-method designs to test key assumptions about social science causation. 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 a wide range of statistical and qualitative tools, and develops over a dozen multi-method designs to test key assumptions about social science causation. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9781107097711
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Hardcover. Etat : new. Hardcover. Reflecting the rising popularity of research that combines qualitative and quantitative social science, Multi-Method Social Science provides the first systematic guide to designing multi-method research. It argues that methods can be productively combined using the framework of integrative multi-method research, with one method used to carry out a final causal inference, and methods from other traditions used to test the key assumptions involved in that causal inference. In making this argument, Jason Seawright considers a wide range of statistical tools including regression, matching, and natural experiments. The book also discusses qualitative tools including process tracing, the use of causal process observations, and comparative case study research. Along the way, the text develops over a dozen multi-method designs to test key assumptions about social science causation. 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 a wide range of statistical and qualitative tools, and develops over a dozen multi-method designs to test key assumptions about social science causation. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9781107097711
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Hardcover. Etat : new. Hardcover. Reflecting the rising popularity of research that combines qualitative and quantitative social science, Multi-Method Social Science provides the first systematic guide to designing multi-method research. It argues that methods can be productively combined using the framework of integrative multi-method research, with one method used to carry out a final causal inference, and methods from other traditions used to test the key assumptions involved in that causal inference. In making this argument, Jason Seawright considers a wide range of statistical tools including regression, matching, and natural experiments. The book also discusses qualitative tools including process tracing, the use of causal process observations, and comparative case study research. Along the way, the text develops over a dozen multi-method designs to test key assumptions about social science causation. 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 a wide range of statistical and qualitative tools, and develops over a dozen multi-method designs to test key assumptions about social science causation. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781107097711
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