Abstract

Previous research on the nature of ability-performance relationships has found the relationship to be linear. Recent Monte Carlo work suggests that the test of the significance of the difference between the Pearson correlation and the correlation ratio (eta), used in previous research, has low power to detect nonlinear relationships. Using 174 studies of the relationship between 9 scales of the General Aptitude Test Battery and job performance, with a mean sample size of 210, and using a power polynomial approach, which has been shown to have higher power than the r vs. eta test, the issue of linearity was reexamined

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