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Bill Shipley
Cause and Correlation in Biology: A User's Guide to Path Analysis, Structural Equations and Causal Inference with R
Cause and Correlation in Biology: A User's Guide to Path Analysis, Structural Equations and Causal Inference with R
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- More about Cause and Correlation in Biology: A User's Guide to Path Analysis, Structural Equations and Causal Inference with R
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.
- Publication date: 13 August 2026
- Page count: 412
- Publisher: Cambridge University Press
- Format: Hardback
- ISBN-13: 9781009560399
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