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Predicting Fluid Intelligence by Components of Reaction Time Distributions from Simple Choice Reaction Time Tasks

Yoanna Schulz-Zhecheva, Manuel C. Voelkle, André Beauducel, Monica Biscaldi, Christoph Klein
Published: 18 July 2016
 by  MDPI
Journal of Intelligence , Volume 4; doi:10.3390/jintelligence4030008

Abstract: Mean reaction times (RT) and the intra-subject variability of RT in simple RT tasks have been shown to predict higher-order cognitive abilities measured with psychometric intelligence tests. To further explore this relationship and to examine its generalizability to a sub-adult-aged sample, we administered different choice RT tasks and Cattell’s Culture Fair Intelligence Test (CFT 20-R) to n = 362 participants aged eight to 18 years. The parameters derived from applying Ratcliff’s diffusion model and an ex-Gaussian model to age-residualized RT data were used to predict fluid intelligence using structural equation models. The drift rate parameter of the diffusion model, as well as σ of the ex-Gaussian model, showed substantial predictive validity regarding fluid intelligence. Our findings demonstrate that stability of performance, more than its mere speed, is relevant for fluid intelligence and we challenge the universality of the worst performance rule observed in adult samples.
Keywords: Fluid Intelligence / reaction time distributions / diffusion model / Ex-gaussian Model

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