Expanding G-Theory Models to Incorporate Congeneric Relationships: Illustrations Using the Big Five Inventory

Abstract

We used structural equation modeling techniques to expand traditional generalizability theory (G-theory) models to allow for congeneric relationships among item responses while accounting for the primary sources of measurement error that affect results from objectively scored, self-report measures. Data came from 919 respondents who completed the Agreeableness, Conscientiousness, Extraversion, Neuroticism, and Openness subscales of the Big Five Inventory (BFI; John et al., 1991) on two occasions. When compared to traditional and factor-based essential tau-equivalent G-theory models, congeneric models on average yielded superior fit statistics, higher estimates of reliability, and lower estimates of transient and specific-factor measurement error. Essential tau-equivalent and congeneric factor models also were configured to allow for simultaneous partitioning of systematic and measurement error variance at both total score and individual item levels. We provide detailed guidelines, examples, and computer code in R for all models discussed in an extended online supplement to enable readers to apply the demonstrated techniques.