Book contents
- Frontmatter
- Contents
- Preface
- 1 Preliminaries
- 2 From cause to correlation and back
- 3 Sewall Wright, path analysis and d-separation
- 4 Path analysis and maximum likelihood
- 5 Measurement error and latent variables
- 6 The structural equations model
- 7 Nested models and multilevel models
- 8 Exploration, discovery and equivalence
- Appendix
- References
- Index
4 - Path analysis and maximum likelihood
Published online by Cambridge University Press: 10 December 2009
- Frontmatter
- Contents
- Preface
- 1 Preliminaries
- 2 From cause to correlation and back
- 3 Sewall Wright, path analysis and d-separation
- 4 Path analysis and maximum likelihood
- 5 Measurement error and latent variables
- 6 The structural equations model
- 7 Nested models and multilevel models
- 8 Exploration, discovery and equivalence
- Appendix
- References
- Index
Summary
James Burke (1996), in his fascinating book, The pinball effect, demonstrates the curious and unexpected paths of influence leading to most scientific discoveries. People often speak of the ‘marriage of ideas’. If so then the most prolific intellectual offspring come, not from the arranged marriages preferred by research administrators, but from chance meetings and even illicit unions. The popular view of scientific discoveries as being linear causal chains from idea to solution is profoundly wrong; a better image would be a tangled web with many dead ends and broken strands. If most present knowledge depends on unlikely chains of events and personalities, then what paths of discovery have been deflected because the right people did not come together at the right time? Which historical developments in science have been changed because two people, each with half of the solution, were prevented from communicating due to linguistic or disciplinary boundaries? The second stage in the development of modern structural equation modelling is a case study in such historical contingencies and interdisciplinary incomprehension.
During the First World War, and in connection with the American war effort, Sewall Wright was on a committee allocating pork production to various US states on the basis of the availability of corn. He was confronted with a problem that had a familiar feel. Given a whole series of variables related to corn availability and pork production, how do all these variables interact to determine the relationship between supply and demand, and the fluctuations between these two? It occurred to him that his new method of path analysis might help.
- Type
- Chapter
- Information
- Cause and Correlation in BiologyA User's Guide to Path Analysis, Structural Equations and Causal Inference, pp. 100 - 135Publisher: Cambridge University PressPrint publication year: 2000
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