This new 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, semiparametric 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 will help to stimulate ideas for further research for many years to come. Based on material presented at the 22nd biennial conference of the Society for Multivariate Analysis in the Behavioral Sciences (SMABS), 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. As such, the chapters are aimed at a broad audience concerned with the latest developments and techniques related to latent variable and latent structure models.
A working knowledge of basic multivariate statistics and measurement theory is assumed.