Full Description
Aimed at practising biologists, especially graduate students and researchers in ecology, this revised and expanded 3rd edition continues to explore cause-effect relationships through a series of robust statistical methods. Every chapter has been updated, and two brand-new chapters cover statistical power, Akaike information criterion statistics and equivalent models, and piecewise structural equation modelling with implicit latent variables. A new R package (pwSEM) is included to assist with the latter. The book offers advanced coverage of essential topics, including d-separation tests and path analysis, and equips biologists with the tools needed to carry out analyses in the open-source R statistical environment. Writing in a conversational style that minimises technical jargon, Shipley offers an accessible text that assumes only a very basic knowledge of introductory statistics, incorporating real-world examples that allow readers to make connections between biological phenomena and the underlying statistical concepts.
Contents
Preface; 1. Cause from correlation?; 2. From cause to correlation and back; 3. Sewall Wright, path analysis and d-separation; 4. Covariance-based SEM without explicit latent variables; 5. Statistical power, AIC statistics and equivalent models; 6. Piecewise SEM with implicit latent variables; 7. Modelling explicit latent variables in covariance-based SEM; 8. Multigroup and multilevel structural equation models; 9. Exploratory structural equations modelling; 10. A cheat sheet of important R functions; References; Index.
