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  • 标题:Predicting Fluid Intelligence by Components of Reaction Time Distributions from Simple Choice Reaction Time Tasks
  • 本地全文:下载
  • 作者:Yoanna Schulz-Zhecheva ; Manuel C. Voelkle ; André Beauducel
  • 期刊名称:Journal of Intelligence
  • 电子版ISSN:2079-3200
  • 出版年度:2016
  • 卷号:4
  • 期号:3
  • 页码:8-19
  • DOI:10.3390/jintelligence4030008
  • 出版社:MDPI Publishing
  • 摘要: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.
  • 关键词:fluid intelligence; reaction time distributions; diffusion model; ex-Gaussian model fluid intelligence ; reaction time distributions ; diffusion model ; ex-Gaussian model
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