22 x 14 cm. Octavo. 107pp. Bound inglossy green boards. Stamp on front free endpaper. Some toning to boards. Includes chapters on: Factor analysis, The LISREL model, and Latent variable models for categorical data. Monographs on Statistics and Applied Probability.

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Detalles bibliogr�ficos

T�tulo

An Introduction to Latent Variable Models

Editor

Chapman and Hall, London and New York

Fecha de publicaci�n

1989

Idioma

Ingl�s

ISBN 10

0412253100

ISBN 13

9780412253102

Encuadernaci�n

Hardcover

Edici�n

First edition.

Estado

Very Good

Cat�logos de vendedores

Mathematics

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Sinopsis

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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