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Thesis (Ph. D.)--University of Rhode Island, 2005. / Typescript. Includes bibliographical references (leaves 69-73).

The present study examined the effects of socio-economic status, quality and level of education on performance on the Wechsler Adult Intelligence Scale 3rd Edition r.:w AIS-III). The study was conducted within the context of the present Human Sciences Research Council (HSRC) W AIS-III standardisation process, cross-cultural psychometric research and the notion of test-wiseness. A South African sample (N = 68) comprising African first language (n = 40) and English first language (n = 28) participants, stratified for age (19 - 30 years), gender and educational attainment (Matric and Graduate) were utilised. Effects due to quality of education were determined by dividing the African language participants into those with private/model C schooling (n = 20) and those with DET schooling (n = 20). Effects due to level of education were determined by dividing the entire sample into those with Matric level education (n = 34) and those with Graduate level education (n = 34). Detailed demographic and socio-economic information were recorded for all participants, who completed the entire American version of the W AIS-III. Results revealed a highly significant positive correlation between high socio-economic status and W AIS-III Full Scale IQ. In addition the respective impact of the relatively poor quality of education and lower level of educational attainment on W AIS-III performance was substantial. These results were discussed in terms of their implications for cross-cultural research, the HSRC standardisation of the W AIS-III and the practical use of the W AIS-III in neuropsychological assessment.

Correlation between the RPRS total and WAIS FSIQ showed that approximately 43% of the variance in the RPRS total can be accounted for by the variance in the FSIQ. Verbal IQ is not significantly higher correlated with the RPRS total than the Performance IQ (p < .10). Factor analysis of the 6 RPRS subscores resulted in 2 factors. Subsequent factor analysis of the 6 RPRS subscores plus FSIQ and the factor analysis of the 6 RPRS subscores plus PIQ and VIQ showed the first factor to be an intelligence factor accounting for 85% of the common variance. The RPRS variables FL, FM, M and Sh loaded on this factor. The second factor was a nonintelligence factor accounting for 15% of the common variance. Small m is clearly the main determinant of this factor followed by Sh. In addition, the results of 2 exploratory factor analyses are discussed. The first exploratory factor analysis involved 23 variables, namely the 6 RPRS subscores, RPRS total, the 11 WAIS subscales, FSIQ, VIQ, PIQ, VIS and OABD. The second exploratory analysis involved 17 variables, namely the 6 RPRS subscores and the 11 WAIS subscales.

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