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J. Intell. 2016, 4(3), 8; doi:10.3390/jintelligence4030008

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

1
Department of Child and Adolescent Psychiatry, University of Freiburg, Hauptstrasse 8, Freiburg D-79104, Germany
2
Department of Psychology, Humboldt University, Unter den Linden 6, Berlin D-10099, Germany
3
Max Planck Institute for Human Development, Lentzallee 94, Berlin D-14195, Germany
4
Department of Psychology, University of Bonn, Kaiser-Karl-Ring 9, Bonn D-53111, Germany
5
Department of Child and Adolescent Psychiatry, Medical Faculty, University of Cologne, Robert-Koch-Straße 10, Cologne D-50931, Germany
6
School of Psychology, Bangor University, Penrallt Rd, Bangor LL57 2AS, Wales, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Oliver Wilhelm
Received: 20 May 2016 / Revised: 11 July 2016 / Accepted: 13 July 2016 / Published: 18 July 2016
(This article belongs to the Special Issue Mental Speed and Response Times in Cognitive Tests)
View Full-Text   |   Download PDF [693 KB, uploaded 18 July 2016]   |  

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. View Full-Text
Keywords: fluid intelligence; reaction time distributions; diffusion model; ex-Gaussian model fluid intelligence; reaction time distributions; diffusion model; ex-Gaussian model
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Schulz-Zhecheva, Y.; Voelkle, M.C.; Beauducel, A.; Biscaldi, M.; Klein, C. Predicting Fluid Intelligence by Components of Reaction Time Distributions from Simple Choice Reaction Time Tasks. J. Intell. 2016, 4, 8.

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