Factor Analysis and Variance Partitioning in Intelligence Test Research: Clarifying Misconceptions

This article addresses conceptual and methodological shortcomings regarding conducting and interpreting intelligence test factor analytic research that appeared in the Decker, S. L., Bridges, R. M., Luedke, J. C., & Eason, M. J. (2020). Dimensional evaluation of cognitive measures: Methodological confounds and theoretical concerns. Journal of Psychoeducational Assessment. Advance online publication article.

Construct Validity of the WISC-V in Clinical Cases: Exploratory and Confirmatory Factor Analyses of the 10 Primary Subtests

Independent exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) research with the Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V) standardization sample has failed to provide support for the five group factors proposed by the publisher, but there have been no independent examinations of the WISC-V structure among clinical samples. The present study examined the latent structure of the 10 WISC-V primary subtests with a large (N = 2,512), bifurcated clinical sample (EFA, n = 1,256; CFA, n = 1,256). EFA did not support five factors as there were no salient subtest factor pattern coefficients on the fifth extracted factor. EFA indicated a four-factor model resembling the WISC-IV with a dominant general factor. A bifactor model with four group factors was supported by CFA as suggested by EFA. Variance estimates from both EFA and CFA found that the general intelligence factor dominated subtest variance and omega-hierarchical coefficients supported interpretation of the general intelligence factor. In both EFA and CFA, group factors explained small portions of common variance and produced low omega-hierarchical subscale coefficients, indicating that the group factors were of poor interpretive value.