Book contents
- Frontmatter
- Contents
- List of Figures
- List of Tables
- Preface to the Second Edition
- Acknowledgments to the Second Edition
- Acknowledgments to the First Edition
- 1 The Scientific Study of Politics
- 2 The Art of Theory Building
- 3 Evaluating Causal Relationships
- 4 Research Design
- 5 Getting to Know Your Data: Evaluating Measurement and Variations
- 6 Probability and Statistical Inference
- 7 Bivariate Hypothesis Testing
- 8 Bivariate Regression Models
- 9 Multiple Regression: The Basics
- 10 Multiple Regression Model Specification
- 11 Limited Dependent Variables and Time-Series Data
- 12 Putting It All Together to Produce Effective Research
- Appendix A Critical Values of Chi-Square
- Appendix B Critical Values of t
- Appendix C The Λ Link Function for Binomial Logit Models
- Appendix D The Φ Link Function for Binomial Probit Models
- Bibliography
- Index
4 - Research Design
- Frontmatter
- Contents
- List of Figures
- List of Tables
- Preface to the Second Edition
- Acknowledgments to the Second Edition
- Acknowledgments to the First Edition
- 1 The Scientific Study of Politics
- 2 The Art of Theory Building
- 3 Evaluating Causal Relationships
- 4 Research Design
- 5 Getting to Know Your Data: Evaluating Measurement and Variations
- 6 Probability and Statistical Inference
- 7 Bivariate Hypothesis Testing
- 8 Bivariate Regression Models
- 9 Multiple Regression: The Basics
- 10 Multiple Regression Model Specification
- 11 Limited Dependent Variables and Time-Series Data
- 12 Putting It All Together to Produce Effective Research
- Appendix A Critical Values of Chi-Square
- Appendix B Critical Values of t
- Appendix C The Λ Link Function for Binomial Logit Models
- Appendix D The Φ Link Function for Binomial Probit Models
- Bibliography
- Index
Summary
OVERVIEW
Given our focus on causality, what research strategies do political scientists use to investigate causal relationships? Generally speaking, the controlled experiment is the foundation for scientific research. And some political scientists use experiments in their work. However, owing to the nature of our subject matter, most political scientists adopt one of two types of “observational” research designs that are intended to mimic experiments. The cross-sectional observational study focuses on variation across individual units (like people or countries). The time-series observational study focuses on variation in aggregate quantities (like presidential popularity) over time. What is an “experiment” and why is it so useful? How do observational studies try to mimic experimental designs? Most importantly, what are the strengths and weaknesses of each of these three research designs in establishing whether or not causal relationships exist between concepts? That is, how does each one help us to get across the four causal hurdles identified in Chapter 3? Relatedly, we introduce issues concerning the selection of samples of cases to study in which we are not able to study the entire population of cases to which our theory applies. This is a subject that will feature prominently in many of the subsequent chapters.
- Type
- Chapter
- Information
- The Fundamentals of Political Science Research , pp. 69 - 91Publisher: Cambridge University PressPrint publication year: 2013