An Introduction to Latent Variable Models von Everett B.: New (2011)

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Print on Demand pp. 116 22:B&W 5.5 x 8.5 in or 216 x 140 mm (Demy 8vo) Perfect Bound on White w/Gloss Lam.

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Bibliografische Details

Titel: An Introduction to Latent Variable Models
Verlag: Springer
Ver�ffentlichungsdatum: 2011
Sprache: Englisch
ISBN-10: 940108954X
ISBN-13: 9789401089548
Bindung: Softcover
Zustand: New

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Inhaltsangabe

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.

Rese�a del editor

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.

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