Modelling Covariances and Latent Variables Using EQS

by G Dunn, Brian S. Everitt, Andrew Pickles

Overview

This primer has been designed as a self-instructional text which serves to introduce the reader to both the principles of statistical modelling of covariance structures and to the use of the EQS software package. It is divided into three parts - the first covering the basic ideas and language of covariance structure modelling together with an introduction to the EQS package. The second section covers a wide variety of models suitable for cross-sectional and longitudinal data and the final section discusses a wide variety of practical problems. This book should be of interest to researchers in psychology, sociology and medicine who use the EQS software; applied and consultant statisticians.

Product Details

ISBN-13:	9780412489907
Publisher:	Taylor & Francis
Publication date:	08/01/1993
Edition description:	New Edition
Pages:	224
Product dimensions:	6.12(w) x 9.19(h) x (d)

About the Author

Dunn, G; Everitt, Brian S.; Pickles, Andrew

Table of Contents

Foreword — Preface — Acknowledgement and note — Overview — 1 Prelude: The ideas of covariance and of covariance structure — 2 Writing a simple EQS program: learning the language — 3 Statistical modelling in EQS — 4 Confirmatory factor analysis models — 5 Multi trait-multimethod and multiple indicator multiple cause models — 6 Models for longitudinal data — 7 Simultaneous analysis of two or more groups — 8 Common practical problems — References — Index.

Editorial Reviews

"... reading this book would be highly recommended prior to carrying out... analyses."
-Australian & New Zealand Physicist
"In writing this book, the authors have made an important contribution to the applied literature on structural equation modelling... sure to become and invaluable reference... The writing is clear, the exercises are excellent, lots of input and output are included, and the range of topics discussed is large."
-Statistical Methods in Medical Research
"In conclusion, I like the book, use it myself, and recommend it to teachers and students of statistics, as well as applied researchers who wish to learn about covariance modelling. Last but not least, you get good value for the price you pay."
-Computational Statistics

From the Publisher