In Bayesian structural equation modeling (BSEM), prior settings may affect model fit, parameter estimation, and model comparison. This simulation study was to investigate how the priors impact evaluation of relative fit across competing models. The design factors for data generation included sample sizes, factor structures, data distributions, and…

Some problems of multiple-group factor rotation based on the parallel proportional profiles and confactor rotation of R. B. Cattell are described, and several alternative modeling solutions are proposed. Benefits and limitations of the structural-modeling approach to oblique confactor resolution are examined, and opportunities for research are…

This study was designed to explain how Profile Analysis via Multidimensional Scaling (PAMS) could be viewed as a structural equations model (SEM). The study replicated the major profiles extracted from PAMS in the context of the latent variables in SEM. Data involved the Basic Theme Scales of the Strong Campbell Interest Inventory (Campbell and…

This study described an explicit multidimensional scaling (MDS) model for profile data, the Profile Analysis via Multidimensional Scaling (PAMS) model. It also illustrated the application of this model to the study of the structure of cognitive ability patterns using the Woodcock-Johnson Psychoeducational Battery-Revised (WJPB-R; 1989; 1991) and…

Multiple group structural equation modeling was used to analyze structural relationships between latent factors underlying writing-related developmental skills and component writing skills in grades 1 through 6 for 600 students (50 boys and 50 girls at each grade level). Results for handwriting, spelling, and compositional quality are discussed…