β Scribed by B. S. Everitt (auth.)
No coin nor oath required. For personal study only.
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 covariΒ ance and correlation matrices in terms of a small number of unobΒ servable constructs. The emphasis is on the practical application of the procedures rather than on detailed discussion of their matheΒ 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.
Front Matter....Pages i-viii
General introduction....Pages 1-12
Factor analysis....Pages 13-31
The LISREL model....Pages 32-71
Latent variable models for categorical data....Pages 72-88
Some final comments....Pages 89-93
Back Matter....Pages 94-107
Science, general
π SIMILAR VOLUMES
Latent Variable Models is a simply tremendous statistics book. It is masterfully, and authoritatively written, with a touch of humor here and there. It is -- by far -- the best book on structural equations and related models.
This book introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. This approach helps less mathematically inclined students grasp the underlying relationships between path analysis, factor analysis, and structural equation modeling
This book introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. This approach helps less mathematically inclined students grasp the underlying relationships between path analysis, factor analysis, and structural equation modeling
This book introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. This approach helps less mathematically inclined students grasp the underlying relationships between path analysis, factor analysis, and structural equation modeling