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An Introduction to Latent Variable Models [Paperback]

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  • Category: Books (Gardening)
  • Author:  Everett, B.
  • Author:  Everett, B.
  • ISBN-10:  940108954X
  • ISBN-10:  940108954X
  • ISBN-13:  9789401089548
  • ISBN-13:  9789401089548
  • Publisher:  Springer
  • Publisher:  Springer
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Mar-2011
  • Pub Date:  01-Mar-2011
  • SKU:  940108954X-11-SPRI
  • SKU:  940108954X-11-SPRI
  • Item ID: 100948365
  • List Price: $54.99
  • Seller: ShopSpell
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  • Delivery by: Jul 04 to Jul 06
  • Notes: Brand New Book. Order Now.
Latent variable models are used in many areas of the social and behavioural sciences, and the increasing availability of computer packages for fitting such models is likely to increase their popularity. This book attempts to introduce such models to applied statisticians and research workers interested in exploring the structure of covari? ance and correlation matrices in terms of a small number of unob? servable constructs. The emphasis is on the practical application of the procedures rather than on detailed discussion of their mathe? matical and statistical properties. It is assumed that the reader is familiar with the most commonly used statistical concepts and methods, particularly regression, and also has a fair knowledge of matrix algebra. My thanks are due to my colleagues Dr David Hand and Dr Graham Dunn for helpful comments on the book, to Mrs Bertha Lakey for her careful typing of a difficult manuscript and to Peter Cuttance for assistance with the LlSREL package. In addition the text clearly owes a great deal to the work on structural equation models published by Karl Joreskog, Dag Sorbom, Peter Bentler, Michael Browne and others.Latent variable models are used in many areas of the social and behavioural sciences, and the increasing availability of computer packages for fitting such models is likely to increase their popularity. This book attempts to introduce such models to applied statisticians and research workers interested in exploring the structure of covari? ance and correlation matrices in terms of a small number of unob? servable constructs. The emphasis is on the practical application of the procedures rather than on detailed discussion of their mathe? matical and statistical properties. It is assumed that the reader is familiar with the most commonly used statistical concepts and methods, particularly regression, and also has a fair knowledge of matrix algebra. My thanks are due to my colleagues Dr David Hand and Dr Graham Dunn for helpful coml3%
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