Cause and Correlation in Biology: A User's Guide to Path Analysis, Structural Equations and Causal Inference with R
Autor Bill Shipleyen Limba Engleză Paperback – 17 apr 2016
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Specificații
ISBN-13: 9781107442597
ISBN-10: 1107442591
Pagini: 314
Ilustrații: 113 b/w illus. 22 tables
Dimensiuni: 173 x 246 x 15 mm
Greutate: 0.63 kg
Ediția:2Revizuită
Editura: Cambridge University Press
Colecția Cambridge University Press
Locul publicării:New York, United States
ISBN-10: 1107442591
Pagini: 314
Ilustrații: 113 b/w illus. 22 tables
Dimensiuni: 173 x 246 x 15 mm
Greutate: 0.63 kg
Ediția:2Revizuită
Editura: Cambridge University Press
Colecția Cambridge University Press
Locul publicării:New York, United States
Cuprins
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. Multigroup models, multilevel models, and corrections for non-independence of observations; 8. Exploration, discovery and equivalence; Index.
Recenzii
Review of previous edition: '… the perfect introduction to SEM. This book can be used as the primary text in a SEM course given within any discipline, and can be used by scholars and researchers from any area of science.' Structural Equation Modeling
Review of previous edition: 'Addressing students and practising biologists, Shipley does a terrific job of making mathematical ideas accessible … Cause and Correlation in Biology is a nontechnical and honest introduction to statistical methods for testing causal hypotheses.' Johan Paulsson, Nature Cell Biology
Review of previous edition: 'I highly recommend the book for those interested in multivariate approaches to biology.' Annals of Botany
'Bill Shipley has done an excellent job in tackling the fundamental issue of testing causality in biology and making it accessible to any biology student or scholar. This book is about statistics, but the storytelling is for biologists. When the first edition for this book came out, in 2000, path analyses were not a common tool for biologists. Although the first edition convinced us to use structural equation modelling, this second edition supplies the essential toolbox. This book is the best route to take if you want to master structural equation modelling in biology, and the very good news is that this second edition not only provides updates and extensions, it also offers R codes to run your analyses.' Anne Charmantier, Centre d'Écologie Fonctionnelle et Évolutive (CEFE), Montpellier
'For a long time biologists have inferred causation only from carefully designed experiments. Shipley's book broadens horizons by showing how to use observational data to infer whether a causal model is plausible, and to estimate the variation in response due to competing causes.' David Warton, University of New South Wales, Sydney
Review of previous edition: 'Addressing students and practising biologists, Shipley does a terrific job of making mathematical ideas accessible … Cause and Correlation in Biology is a nontechnical and honest introduction to statistical methods for testing causal hypotheses.' Johan Paulsson, Nature Cell Biology
Review of previous edition: 'I highly recommend the book for those interested in multivariate approaches to biology.' Annals of Botany
'Bill Shipley has done an excellent job in tackling the fundamental issue of testing causality in biology and making it accessible to any biology student or scholar. This book is about statistics, but the storytelling is for biologists. When the first edition for this book came out, in 2000, path analyses were not a common tool for biologists. Although the first edition convinced us to use structural equation modelling, this second edition supplies the essential toolbox. This book is the best route to take if you want to master structural equation modelling in biology, and the very good news is that this second edition not only provides updates and extensions, it also offers R codes to run your analyses.' Anne Charmantier, Centre d'Écologie Fonctionnelle et Évolutive (CEFE), Montpellier
'For a long time biologists have inferred causation only from carefully designed experiments. Shipley's book broadens horizons by showing how to use observational data to infer whether a causal model is plausible, and to estimate the variation in response due to competing causes.' David Warton, University of New South Wales, Sydney
Descriere
A complete user's guide to structural equations explaining the underlying principals and practical implementation of these methods.