Using Structural Equation Modeling to Reproduce and Extend ANOVA-Based Generalizability Theory Analyses for Psychological Assessments

Generalizability theory provides a comprehensive framework for determining how multiple sources of measurement error affect scores from psychological assessments and using that information to improve those assessments. Although generalizability designs have traditionally been analyzed analyses variance (ANOVA) procedures, the same can be replicated extended structural equation models. We collected multi-occasion data inventories measuring numerous dimensions personality, self-concept, socially desirable responding compare components, coefficients, dependability proportions universe score modeling versus ANOVA techniques. further applied techniques continuous latent response variable metrics derived Monte Carlo-based confidence intervals indices on both observed metrics. Results estimated procedures seldom varied. Differences in reliability between raw were much greater scales with dichotomous responses, thereby highlighting value doing evaluate gains might achieved by increasing options. provide detailed guidelines applying demonstrated ANOVA-based statistical software.