The SAGE Handbook of Research Methods in Political Science and International Relations offers a comprehensive overview of research processes in social science - from the ideation and design of research projects, through the construction of theoretical arguments, to conceptualization, measurement, and data collection, and quantitative and qualitative empirical analysis - exposited through 65 major new contributions from leading international methodologists. Each chapter surveys, builds upon, and extends the modern state of the art in its area. Following through its six-part organization, undergraduate and graduate students, researchers and practicing academics will be guided through the design, methods, and analysis of issues in Political Science and International Relations: Part One: Formulating Good Research Questions and Designing Good Research Projects; Part Two: Methods of Theoretical Argumentation; Part Three: Conceptualization and Measurement; Part Four: Large-Scale Data Collection and Representation Methods; Part Five: Quantitative-Empirical Methods; Part Six: Qualitative and Mixed Methods.

Network Modeling: Estimation, Inference, Comparison, and Selection

Network Modeling: Estimation, Inference, Comparison, and Selection

John P. SchoenemanBruce A. Desmarais


Which international trade relationships are most likely to break down over the next decade? What predicts the level of cross-party collaboration in a legislature? Do online political discussion networks constitute as echo chambers? What these questions have in common is that they address systems of political relationships (trade, lawmaking, political communication) – systems that can be represented as networks in which political actors constitute the nodes, and the relationships constitute the edges between the nodes. Inferential network analysis represents a methodological class that can be drawn upon to answer questions like these. Most statistical models used in the social sciences rely on the assumption that the observations in a dataset (or at least ...

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