Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- Preface to the second edition
- 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 equation model
- 7 Multigroup models, multilevel models and corrections for the non-independence of observations
- 8 Exploration, discovery and equivalence
- Appendix A cheat-sheet of useful R functions
- References
- Index
Preface to the second edition
Published online by Cambridge University Press: 05 April 2016
- Frontmatter
- Dedication
- Contents
- Preface
- Preface to the second edition
- 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 equation model
- 7 Multigroup models, multilevel models and corrections for the non-independence of observations
- 8 Exploration, discovery and equivalence
- Appendix A cheat-sheet of useful R functions
- References
- Index
Summary
I had two motives, one positive and one more selfish, in writing the first edition of this book. The positive motive was to provide a detailed introduction of these methods to practising biologists, since they were largely unknown to students and researchers in this discipline. The more selfish motive was to provide a detailed justification of these methods to practising biologists. You see, I was frustrated. My research manuscripts that included these methods were being rejected by reviewers, who viewed the analyses as the statistical equivalents of conjurer's tricks. I concluded that a book-length explanation that was written specifically for biologists would provide such a justification. Now, writing fifteen years later, the situation is quite different. These methods have been increasingly adopted by biologists working in ecology, evolution, genetics and molecular biology. I hope that the first edition of this book, as well as Jim Grace's (2006) very fine book, have contributed to this change. Virtually every chapter has been updated in this second edition. These changes include, inter alia, new additions to the d-sep test, the inclusion of phylogenetic information and an expanded treatment of latent variables. The most extensive change is the detailed explanation for implementing these methods using the R programming language. The only computer programs for structural equation modelling that were available when I wrote the first edition were commercial ones. Since I didn't want to become a salesman for any particular commercial package, I didn't include the actual code and steps for carrying out the analyses. However, a ‘user's guide’ that omits such vital information is clearly lacking. Now that the freely available R program has become so ubiquitous for statistical analysis by biologists, and now that the methods in this book have been included in several R libraries, I have included detailed instructions in this second edition for carrying out the analyses.
- Type
- Chapter
- Information
- Cause and Correlation in BiologyA User's Guide to Path Analysis, Structural Equations and Causal Inference with R, pp. xiiiPublisher: Cambridge University PressPrint publication year: 2016