Abstract
The purpose of the current study is to compare the extent to which general and specific abilities predict academic performances that are also varied in breadth (i.e., general performance and specific performance). The general and specific constructs were assumed to vary only in breadth, not order, and two data analytic approaches (i.e., structural equation modeling [SEM] and relative weights analysis) consistent with this theoretical assumption were compared. Conclusions regarding the relative importance of general and specific abilities differed based on data analytic approaches. The SEM approach identified general ability as the strongest and only significant predictor of general academic performance, with neither general nor specific abilities predicting any of the specific subject grade residuals. The relative weights analysis identified verbal reasoning as contributing more than general ability, or other specific abilities, to the explained variance in general academic performance. Verbal reasoning also contributed to most of the explained variance in each of the specific subject grades. These results do not provide support for the utility of predictor-criterion alignment, but they do provide evidence that both general and specific abilities can serve as useful predictors of performance.
Highlights
Measures of cognitive ability consistently correlate positively with other measures of cognitive ability
I considered the incremental fit index provided by the comparative fit index (CFI; [37]), which compares the observed covariance matrix to a baseline model with uncorrelated latent variables, and the absolute fit indices provided by the root mean square error of approximation (RMSEA; [38]) and the standardized root mean square residual (SRMR; [39])
Correlations among the ability factors were all positive (M = 0.56; range: 0.32 to 0.86), with the highest correlations being between general ability and the specific abilities
Summary
Measures of cognitive ability consistently correlate positively with other measures of cognitive ability. 91), is whether breadth only (as represented by the nested-factors model), or super-ordination (as represented by the higher-order factor model), defines the general ability factor in relation to the specific ability factors. As an extension of Spearman’s original unidimensional model of cognitive ability, higher-order factor models assume that the higher-order factor (i.e., general ability) explains the positive correlations among lower-order factors (i.e., specific abilities) [7]. That is, both breadth and superordinate position define the theoretical relations between general and specific abilities. General ability is conceptualized more broadly than specific abilities, and because of its causal status, it is of a higher order
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