Latent Variable Models and Factor Analysis (Kendall's Library of Statistics) - Softcover

Bartholomew, D. J.; Knott, M.

9780340692431: Latent Variable Models and Factor Analysis (Kendall's Library of Statistics)

Softcover

ISBN 10: 034069243X ISBN 13: 9780340692431

Publisher: Hodder Education Publishers, 1999

Latent variables, variables that cannot be observed directly, have numerous applications, particularly in psychometrics and sociology, and this new edition provides a comprehensive and unified treatment. Extensively revised and including much recent work, the book develops a framework for handling latent variables with standard statistical methods. It includes an introductory chapter, followed by a careful development of the General Linear Latent Variable Model (GLLVM). A large class of latent variable models turns out to be special cases of GLLVM, and the book devotes a number of chapters to specific models. The treatment aims to be mathematically complete and emphasizes questions of precision and goodness of fit. The book features numerous examples and concludes with a critique of some of the popular and widely used linear models.

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From the Back Cover:

Hitherto latent variable modelling has hovered on the fringes of the statistical mainstream but if the purpose of statistics is to deal with real problems, there is every reason for it to move closer to centre stage. In the social sciences especially, latent variables are common and if they are to be handled in a truly scientific manner, statistical theory must be developed to include them. This book aims to show how that should be done.

This second edition is a complete re-working of the book of the same name which appeared in the Griffin’s Statistical Monographs in 1987. Since then there has been a surge of interest in latent variable methods which has necessitated a radical revision of the material but the prime object of the book remains the same. It provides a unified and coherent treatment of the field from a statistical perspective. This is achieved by setting up a sufficiently general framework to enable the derivation of the commonly used models. The subsequent analysis is then done wholly within the realm of probability calculus and the theory of statistical inference. Numerical examples are provided as well as the software to carry them out ( where this is not otherwise available). Additional data sets are provided in some cases so that the reader can aquire a wider experience of analysis and interpretation.

About the Author:

David Bartholomew is Professor of Statistics at the London School of Economics.

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