Based on material presented at the 22nd conference of the Society for Multivariate Analysis in the Behavioral Sciences (July 2000), these 12 papers describe original research and developments concerned with latent variable modeling and structural equation modeling. Each chapter assumes that the reader has already mastered basic multivariate statistics and measurement theory. Topics covered include hierarchically related nonparametric IRT models and practical data analysis methods, fully semiparametric estimation of the two-parameter latent trait model for binary data, exploring structural equation model misspecifications via latent individual residuals, and using predicted latent scores in general latent structure models. Annotation c. Book News, Inc., Portland, OR (booknews.com)
This edited volume features cutting-edge topics from the leading researchers in the areas of latent variable modeling. Content highlights include coverage of approaches dealing with missing values, semi-parametric estimation, robust analysis, hierarchical data, factor scores, multi-group analysis, and model testing. New methodological topics are illustrated with real applications. The material presented brings together two traditions: psychometrics and structural equation modeling. Latent Variable and Latent Structure Models' thought-provoking chapters from the leading researchers in the area will help to stimulate ideas for further research for many years to come.
This volume will be of interest to researchers and practitioners from a wide variety of disciplines, including biology, business, economics, education, medicine, psychology, sociology, and other social and behavioral sciences. A working knowledge of basic multivariate statistics and measurement theory is assumed.
