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Cause and Correlation in Biology : =...
~
Shipley, Bill.
Cause and Correlation in Biology : = A User's Guide to Path Analysis, Structural Equations and Causal Inference.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Cause and Correlation in Biology :/
Reminder of title:
A User's Guide to Path Analysis, Structural Equations and Causal Inference.
Author:
Shipley, Bill.
Published:
Cambridge :Cambridge University Press, : 2000.,
Description:
329 p.
Subject:
Biometry. -
Online resource:
Click here to view book
ISBN:
9780511605949 (electronic bk.)
Cause and Correlation in Biology : = A User's Guide to Path Analysis, Structural Equations and Causal Inference.
Shipley, Bill.
Cause and Correlation in Biology :
A User's Guide to Path Analysis, Structural Equations and Causal Inference.[electronic resource]. - Cambridge :Cambridge University Press,2000. - 329 p.
Cover; Half-title; Title; Copyright; Dedication; 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
Written in a jargon-free, conversational style, this book explores the relationship between correlation and causation. It presents a series of statistical methods that can test, and potentially discover, cause-effect relationships between variables in situations in which it is not possible to conduct controlled experiments.
Electronic reproduction.
Available via World Wide Web.
Mode of access: World Wide Web.
ISBN: 9780511605949 (electronic bk.)Subjects--Topical Terms:
85606
Biometry.
Index Terms--Genre/Form:
96803
Electronic books.
LC Class. No.: QH323.5
Dewey Class. No.: 570/.1/5195
Cause and Correlation in Biology : = A User's Guide to Path Analysis, Structural Equations and Causal Inference.
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A User's Guide to Path Analysis, Structural Equations and Causal Inference.
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2000.
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Cambridge University Press,
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329 p.
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Cover; Half-title; Title; Copyright; Dedication; 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
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Written in a jargon-free, conversational style, this book explores the relationship between correlation and causation. It presents a series of statistical methods that can test, and potentially discover, cause-effect relationships between variables in situations in which it is not possible to conduct controlled experiments.
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Available via World Wide Web.
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Biometry.
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Click here to view book
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http://ebooks.cambridge.org/ebook.jsf?bid=CBO9780511605949
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