Conjectures and refutations in cognitive ability structural validity research: Insights from Bayesian structural equation modeling

Abstract

The use of Bayesian structural equation modeling (BSEM) provided additional insight into the WISC–V theoretical structure beyond that offered by traditional factor analytic approaches (e.g., exploratory factor analysis and maximum likelihood confirmatory factor analysis) through the specification of all cross loadings and correlated residual terms. The results indicated that a five-factor higher-order model with a correlated residual between the Visual-Spatial and Fluid Reasoning group factors provided a superior fit to the four bifactor model that has been preferred in prior research. There were no other statistically significant correlated residual terms or cross loadings in the measurement model. The results further suggest that the WISC–V ten subtest primary battery readily attains simple structure and its index level scores may be interpreted as suggested in the WISC–V's scoring and interpretive manual. Moreover, BSEM may help to advance IQ theory by providing contemporary intelligence researchers with a novel tool to explore complex interrelationships among cognitive abilities—relationships that traditional structural equation modeling methods may overlook. It can also help attenuate the replication crises in school psychology within the area of cognitive assessment structural validity research through systematic evaluation of complex structural relationships obviating the need for CFA based post hoc specification searches which can be prone to confirmation bias and capitalization on chance.