Next Article in Journal / Special Issue
Predicting Fluid Intelligence by Components of Reaction Time Distributions from Simple Choice Reaction Time Tasks
Previous Article in Journal
Spearman’s Hypothesis Tested on Black Adults: A Meta-Analysis
Previous Article in Special Issue
Validity of the Worst Performance Rule as a Function of Task Complexity and Psychometric g: On the Crucial Role of g Saturation
Article

Trait Characteristics of Diffusion Model Parameters

Institute of Psychology, Heidelberg University, Hauptstr. 47-51, D-69117 Heidelberg, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Oliver Wilhelm
Received: 31 March 2016 / Revised: 30 June 2016 / Accepted: 8 July 2016 / Published: 18 July 2016
(This article belongs to the Special Issue Mental Speed and Response Times in Cognitive Tests)
Cognitive modeling of response time distributions has seen a huge rise in popularity in individual differences research. In particular, several studies have shown that individual differences in the drift rate parameter of the diffusion model, which reflects the speed of information uptake, are substantially related to individual differences in intelligence. However, if diffusion model parameters are to reflect trait-like properties of cognitive processes, they have to qualify as trait-like variables themselves, i.e., they have to be stable across time and consistent over different situations. To assess their trait characteristics, we conducted a latent state-trait analysis of diffusion model parameters estimated from three response time tasks that 114 participants completed at two laboratory sessions eight months apart. Drift rate, boundary separation, and non-decision time parameters showed a great temporal stability over a period of eight months. However, the coefficients of consistency and reliability were only low to moderate and highest for drift rate parameters. These results show that the consistent variance of diffusion model parameters across tasks can be regarded as temporally stable ability parameters. Moreover, they illustrate the need for using broader batteries of response time tasks in future studies on the relationship between diffusion model parameters and intelligence. View Full-Text
Keywords: mental speed; diffusion model; latent state-trait theory; response times; drift rate; boundary separation; non-decision time; temporal stability mental speed; diffusion model; latent state-trait theory; response times; drift rate; boundary separation; non-decision time; temporal stability
Show Figures

Figure 1

MDPI and ACS Style

Schubert, A.-L.; Frischkorn, G.T.; Hagemann, D.; Voss, A. Trait Characteristics of Diffusion Model Parameters. J. Intell. 2016, 4, 7. https://doi.org/10.3390/jintelligence4030007

AMA Style

Schubert A-L, Frischkorn GT, Hagemann D, Voss A. Trait Characteristics of Diffusion Model Parameters. Journal of Intelligence. 2016; 4(3):7. https://doi.org/10.3390/jintelligence4030007

Chicago/Turabian Style

Schubert, Anna-Lena, Gidon T. Frischkorn, Dirk Hagemann, and Andreas Voss. 2016. "Trait Characteristics of Diffusion Model Parameters" Journal of Intelligence 4, no. 3: 7. https://doi.org/10.3390/jintelligence4030007

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop