Examination of differential effects of cognitive abilities on reading and mathematics achievement across race and ethnicity: Evidence with the WJ IV.
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There has been little research investigating the predictive validity of modern intelligence tests for racially and ethnically diverse students. The validity of test score interpretation within educational and psychological assessment assumes that test scores predict educationally relevant phenomena equally well for individuals, regardless of group membership (American Educational Research Association et al., 2014; Messick, 1995; Warne et al., 2014). We used multiple group latent variable structural equation modeling (SEM) to investigate Cattell-Horn-Carroll general (g) and broad cognitive abilities on reading and mathematics achievement and whether these differed between racial (African American, Asian, and Caucasian) and ethnic (Hispanic, non-Hispanic) children and adolescents within the Woodcock-Johnson IV norming sample (N=3127). After establishing construct equivalence across racial and ethnic groups, supporting the consistent calculation of composite scores regardless of group membership, we then examined the predictive validity of intelligence on achievement. After controlling for parent education, findings suggested two instances of differential predictive relations: (a) general intelligence had larger influences on basic reading skills for Caucasians when compared to Asian peers, and (b) comprehension-knowledge had larger influences on basic reading skills for Asians when compared to Caucasian peers. The overall pattern of findings suggests there is little to no predictive bias with the WJ IV. However, the findings indicate that when latent mean differences exist (after establishing strong factorial invariance), then bias will be introduced into the estimation of regression parameters used to identify differential predictive validity. Thus, even when measurement invariance is supported, differential prediction bias is inevitable when there are mean differences in the scores used as predictors. Future test bias research should consider latent ability differences and how that may impact findings of bias, and possibly, socioeconomic status-related indicators when assessing for measurement or prediction bias in intelligence and achievement tests.
author list (cited authors)
Hajovsky, D. B., & Chesnut, S. R.
complete list of authors
Hajovsky, Daniel B||Chesnut, Steven R