Volume 1
Preface: So You're A Grad Student Now? Maybe You Should Do This
Part I Formulating Good Research Questions and Designing Good Research Projects
1. Asking Interesting Questions
2. From Questions and Puzzles to Research Project
3. The Simple, the Trivial and the Insightful: Field Dispatches from a Formal Theorist
4. Evidence-Driven Computational Modeling
5. Taking Data Seriously in the Design of Data Science Projects
6. Designing Qualitative Research Projects: Notes on Theory Building, Case Selection and Field Research
7. Theory Building for Causal Inference: EITM Research Projects
8. EITM: Applications in Political Science and International Relations
Part II Methods of Theoretical Argumentation
9. Political Psychology, Social Psychology and Behavioral Economics
10. Institutional Theory and Method
11. Applied Game Theory: An Overview and First Thoughts on the Use of Game Theoretic Tools
12. The Spatial Voting Model
13. New Directions in Veto Bargaining: Message Legislation, Virtue Signaling, and Electoral Accountability
14. Models of Coalition Politics: Recent Developments and New Directions
15. Models of Interstate Conflict
16. Models of the Judiciary
17. Wrestling with Complexity in Computational Social Science: Theory, Estimation and Representation
18. Learning and Diffusion Models
Part III Conceptualization and Measurement
19. Conceptualization and Measurement: Basic Distinctions and Guidelines
20. Measurement Models
21. Measuring Attitudes – Multilevel Modeling with Post-Stratification (MrP)
Part IV Large-Scale Data Collection and Representation Methods
22. Web Data Collection: Potentials and Challenges
23. How to Use Social Media Data for Political Science Research
24. Spatial Data
25. Visualizing Data in Political Science
26. Text as Data: An Overview
27. Scaling Political Positions from Text: Assumptions, Methods and Pitfalls
28. Classification and Clustering
29. Sentiment Analysis and Social Media
30. Big Relational Data: Network-Analytic Measurement
Volume 2
Part V Quantitative-Empirical Methods
31. Econometric Modeling: From Measurement, Prediction, and Causal Inference to Causal-Response Estimation
32. A Principled Approach to Time Series Analysis
33. Time-Series-Cross-Section Analysis
34. Dynamic Systems of Equations
35. Duration Analysis
36. Multilevel Analysis
37. Selection Bias in Political Science and International Relations Applications
38. Dyadic Data Analysis
39. Model Specification and Spatial Interdependence
40. Instrumental Variables: From Structural Equation Models to Design-Based Causal Inference
41. Causality and Design-Based Inference
42. Statistical Matching with Time-Series Cross-Sectional Data: Magic, Malfeasance, or Something in between?
43. Differences-in-Differences: Neither Natural nor an Experiment
44. The Regression Discontinuity Design
45. Network Analysis: Theory and Testing
46. Network Modeling: Estimation, Inference, Comparison, and Selection
47. Bayesian Methods in Political Science
48. Bayesian Ideal Point Estimation
49. Bayesian Model Selection, Model Comparison, and Model Averaging
50. Bayesian Modeling and Inference: A Postmodern Perspective
51. Laboratory Experimental Methods
52. Field Experiments on the Frontier: Designing Better
53. Field Experiments, Theory, and External Validity
54. Survey Experiments and the Quest for Valid Interpretation
55. Deep Learning for Political Science
56. Machine Learning in Political Science: Supervised Learning Models
Part VI Qualitative and ‘Mixed’ Methods
57. Set Theoretic Methods
58. Mixed-Methods Designs
59. Case Study Methods: Case Selection and Case Analysis
60. Comparative Analyses of Foreign Policy
61. When Talk Isn't Cheap: Opportunities and Challenges in Interview Research
62. Focus Groups: From Qualitative Data Generation to Analysis
63. Interpretive Approaches in Political Science and International Relations
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