A statistical method that will appeal to two groups in particular - those who are currently using the more traditional technique of exploratory factor analysis and those who are interested in the analysis of covariance structures, commonly known as the LISREL model. The first group will find that this technique may be more appropriate to the analysis of their research problems while the second group will find that confirmatory factor analysis is a useful first step to understanding the LISREL model. This book, and its companion volume, "Covariance Structure Models," are designed to be read...
A statistical method that will appeal to two groups in particular - those who are currently using the more traditional technique of exploratory fac...
While many readers may be unfamiliar with the full complexity of the covariance structure model, many may have mastered at least one of its two components, each of which is a powerful and well-known statistical technique in its own right. The first is the confirmatory factor model frequently used in psychometrics; the second, the structural equation model, is familiar to econometricians. The discussion in this volume will be particularly useful for estimating models with equality constraints and correlated errors across some but not all equations. The final chapter includes a guide to...
While many readers may be unfamiliar with the full complexity of the covariance structure model, many may have mastered at least one of its two compon...
What is the role of fit measures when respecifying a model? Should the means of the sampling distributions of a fit index be unrelated to the size of the sample? Is it better to estimate the statistical power of the chi-square test than to turn to fit indices? Exploring these and related questions, well-known scholars examine the methods of testing structural equation models (SEMS) with and without measurement error, as estimated by such programs as EQS, LISREL and CALIS.
What is the role of fit measures when respecifying a model? Should the means of the sampling distributions of a fit index be unrelated to the size of ...
Evaluates the most useful models for categorical and limited dependent variables (CLDVs), emphasizing the links among models and applying common methods of derivation, interpretation, and testing. The author also explains how models relate to linear regression models whenever possible. Annotation c.
Evaluates the most useful models for categorical and limited dependent variables (CLDVs), emphasizing the links among models and applying common metho...
