Book contents
- Frontmatter
- Contents
- List of figures
- List of tables
- Acknowledgments
- 1 Pathway analysis and the elusive search for causal mechanisms
- 2 Preparing for pathway analysis
- 3 Case selection for pathway analysis
- 4 Comparison of case selection approaches
- 5 Regression-based case selection for pathway analysis of non-linear relationships
- 6 Matching to select cases for pathway analysis
- 7 Using large-N methods to gain perspective on prior case studies
- 8 Pathway analysis and future studies of mechanisms
- 9 Conclusion
- Glossary of terms
- References
- Index
8 - Pathway analysis and future studies of mechanisms
Published online by Cambridge University Press: 05 July 2014
- Frontmatter
- Contents
- List of figures
- List of tables
- Acknowledgments
- 1 Pathway analysis and the elusive search for causal mechanisms
- 2 Preparing for pathway analysis
- 3 Case selection for pathway analysis
- 4 Comparison of case selection approaches
- 5 Regression-based case selection for pathway analysis of non-linear relationships
- 6 Matching to select cases for pathway analysis
- 7 Using large-N methods to gain perspective on prior case studies
- 8 Pathway analysis and future studies of mechanisms
- 9 Conclusion
- Glossary of terms
- References
- Index
Summary
Introduction
To this point, we have mainly focused on the early stages of mechanism-centered research, particularly selecting cases for pathway analysis that explore the links underlying an association between some explanatory variable (X1) and an outcome (Y). However, the results of pathway analysis not only can provide a map of mechanisms underlying an X1/Y relationship, but also can be used to “look forward” to provide insight into the feasibility and nature of future studies of mechanisms. From this vantage, pathway analysis is best understood as part of a larger research agenda that spans multiple years, multiple research approaches, and multiple researchers.
The forward-looking purposes of pathway analysis are largely ignored in the literature for a variety of possible reasons. Partly this omission may reflect the limited state of knowledge about mechanisms in many areas. Quantitative studies of mechanisms require that a researcher has already identified some basic information about the mechanisms linking X1 and Y and understand the basic structure of the X1/Y relationship (see Table 2.2 in Chapter 2). This omission also may reflect that the literature on how to study mechanisms quantitatively is relatively new and rapidly evolving. Nevertheless, there are some areas in which researchers have accumulated a considerable amount of insight into mechanisms, and there are compelling reasons for pursuing further mechanism-centered research. For researchers working in such an area, the question to ask is: How might insights from pathway analysis inform future studies on mechanisms?
- Type
- Chapter
- Information
- Finding PathwaysMixed-Method Research for Studying Causal Mechanisms, pp. 117 - 138Publisher: Cambridge University PressPrint publication year: 2014