| Description |
1 online resource (317 pages) : illustrations |
| Contents |
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 |
| Summary |
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 |
| Notes |
Originally published: 2001 |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Print version record |
| Subject |
Biometry.
|
|
Correlation (Statistics)
|
|
Causation.
|
|
biometrics.
|
|
correlation.
|
|
Biometry.
|
|
Causation.
|
|
Correlation (Statistics)
|
| Form |
Electronic book
|
| ISBN |
0511046812 |
|
9780511046810 |
|
0511031548 |
|
9780511031540 |
|
9780511605949 |
|
0511605943 |
|
9780511017728 |
|
0511017723 |
|
9780521791533 |
|
0521791537 |
|
9780521529211 |
|
0521529212 |
|
