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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.
Field research - leaving one's home institution in order to acquire data, information or insights that significantly inform one's research - remains indispensable, even in a digitally networked era. This book, the first of its kind in political science, reconsiders the design and execution of field research and explores its role in producing knowledge. First, it offers an empirical overview of fieldwork in the discipline based on a large-scale survey and extensive interviews. Good fieldwork takes diverse forms yet follows a set of common practices and principles. Second, the book demonstrates the analytic benefits of fieldwork, showing how it contributes to our understanding of politics. Finally, it provides intellectual and practical guidance, with chapters on preparing for field research, operating in the field and making analytic progress while collecting data, and on data collection techniques including archival research, interviewing, ethnography and participant observation, surveys, and field experiments.