Is the Cattell–Horn–Carroll-based factor structure of the Wechsler Intelligence Scale for Children—Fifth Edition (WISC-V) construct invariant for a representative sample of African–American, Hispanic, and Caucasian male and female students ages 6 to 16 years?
Year: 2016
Type: article
Study design: Observational Study
Abstract: Since the inception of testing, the examination of test bias has been discussed and debated in the literature. As new tests are developed or old tests are revised, part of the standardization process involves the examination of gender and ethnic item bias. The exploration of construct invariance across different ethnic and gender groups, however, is not part of the test construction or validation process. This study investigated factorial invariance of the Cattell–Horn–Carroll (CHC)-based factor structure of the most recent version of the Wechsler tests—the Wechsler Intelligence Scale For Children—Fifth Edition (WISC-V; Wechsler 2014a )—across a representative sample of African–American, Hispanic, and Caucasian male and female students ages 6–16 years ( N = 2637). Specifically, confirmatory factor analysis was used to explore whether increasing sets of equality constraints fit the underlying theoretical structure of the WISC-V equally well. Results showed that all five CHC broad abilities, in addition to the general factor g , demonstrated structural invariance for all six ethnic/gender groups. Findings from this study suggest that, despite mean score differences, neuropsychologists can be confident that the WISC-V factor structure is equivalent for the different subgroups and scores are, thus, equally meaningful for African–American, Hispanic, and Caucasian male and female students. These results are of value, given the frequent use of intelligence tests, especially of the WISC-V, when making important and, oftentimes, life-changing decisions regarding diagnosis and access or denial to special programs and classes.
Author: Caroline Scheiber
Institution: Denver Health Medical Center
Language: English
Field: Decision Sciences
Domain: Social Sciences
SDG: Reduced inequalities
Open Access status: bronze
OpenAlex ID: W2510393085