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J. Intell., Volume 4, Issue 3 (September 2016) – 6 articles

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Open AccessArticle
Cognitive Aging in the Seattle Longitudinal Study: Within-Person Associations of Primary Mental Abilities with Psychomotor Speed and Cognitive Flexibility
J. Intell. 2016, 4(3), 12; https://doi.org/10.3390/jintelligence4030012 - 14 Sep 2016
Cited by 2 | Viewed by 4523
Abstract
It has long been proposed that cognitive aging in fluid abilities is driven by age-related declines of processing speed. Although study of between-person associations generally supports this view, accumulating longitudinal between-person and within-person evidence indicates less strong associations between speed and fluid cognitive [...] Read more.
It has long been proposed that cognitive aging in fluid abilities is driven by age-related declines of processing speed. Although study of between-person associations generally supports this view, accumulating longitudinal between-person and within-person evidence indicates less strong associations between speed and fluid cognitive performance. Initial evidence also suggests that cognitive flexibility may explain within-person variability in cognitive performance. In the present study, we used up to nine waves of data over 56 years from a subsample of 582 participants of the Seattle Longitudinal Study to examine (a) within-person associations of psychomotor speed and cognitive flexibility with cognitive aging in primary mental abilities (including inductive reasoning, number ability, verbal meaning, spatial orientation, and word fluency); and (b) how these within-person associations change with age. In line with the processing speed theory, results revealed that within persons, primary mental abilities (including fluid, crystallized, and visualization measures) were indeed associated with psychomotor speed. We also observed age-related increases in within-person couplings between primary mental abilities and psychomotor speed. While the processing speed theory focuses primarily on associations with fluid abilities, age-related increases in coupling were found for a variety of ability domains. Within-person associations between primary mental abilities and cognitive flexibility were weaker and relatively stable with age. We discuss the role of speed and flexibility for cognitive aging. Full article
(This article belongs to the Special Issue Mental Speed and Response Times in Cognitive Tests)
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Open AccessArticle
Sometimes More Is Better, and Sometimes Less Is Better: Task Complexity Moderates the Response Time Accuracy Correlation
J. Intell. 2016, 4(3), 11; https://doi.org/10.3390/jintelligence4030011 - 25 Aug 2016
Cited by 5 | Viewed by 3973
Abstract
This study addresses the relationship between item response time and item accuracy (i.e., the response time accuracy correlation, RTAC) in figural matrices tests. The dual processing account of response time effects predicts negative RTACs in tasks that allow for relatively automatic processing and [...] Read more.
This study addresses the relationship between item response time and item accuracy (i.e., the response time accuracy correlation, RTAC) in figural matrices tests. The dual processing account of response time effects predicts negative RTACs in tasks that allow for relatively automatic processing and positive RTACs in tasks that require controlled processing. Contrary to these predictions, several studies found negative RTACs for reasoning tests. Nevertheless, it was demonstrated that the RTAC is moderated by task complexity (i.e., the interaction between person ability and item difficulty) and that under conditions of high complexity (i.e., low ability and high difficulty) the RTAC was even slightly positive. The goal of this study was to demonstrate that with respect to task complexity the direction of the RTAC (positive vs. negative) can change substantially even within a single task paradigm (i.e., figural matrices). These predictions were tested using a figural matrices test that employs a constructed response format and has a broad range of item difficulties in a sample with a broad range of ability. Confirming predictions, strongly negative RTACs were observed when task complexity was low (i.e., fast responses tended to be correct). With increasing task complexity, the RTAC flipped to be strongly positive (i.e., slow responses tended to be correct). This flip occurred earlier for people with lower ability, and later for people with higher ability. Cognitive load of the items is suggested as an explanation for this phenomenon. Full article
(This article belongs to the Special Issue Mental Speed and Response Times in Cognitive Tests)
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Open AccessArticle
Response Mixture Modeling of Intraindividual Differences in Responses and Response Times to the Hungarian WISC-IV Block Design Test
J. Intell. 2016, 4(3), 10; https://doi.org/10.3390/jintelligence4030010 - 04 Aug 2016
Cited by 6 | Viewed by 4018
Abstract
Response times may constitute an important additional source of information about cognitive ability as it enables to distinguishing between different intraindividual response processes. In this paper, we present a method to disentangle interindividual variation from intraindividual variation in the responses and response times [...] Read more.
Response times may constitute an important additional source of information about cognitive ability as it enables to distinguishing between different intraindividual response processes. In this paper, we present a method to disentangle interindividual variation from intraindividual variation in the responses and response times of 978 subjects to the 14 items of the Hungarian WISC-IV Block Design test. It is found that faster and slower responses differ in their measurement properties suggesting that there are intraindivual differences in the response processes adopted by the subjects. Full article
(This article belongs to the Special Issue Mental Speed and Response Times in Cognitive Tests)
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Open AccessArticle
The Worst Performance Rule as Moderation: New Methods for Worst Performance Analysis
J. Intell. 2016, 4(3), 9; https://doi.org/10.3390/jintelligence4030009 - 20 Jul 2016
Cited by 3 | Viewed by 3996
Abstract
Worst performance in cognitive processing tasks shows larger relationships to general intelligence than mean or best performance. This so called Worst Performance Rule (WPR) is of major theoretical interest for the field of intelligence research, especially for research on mental speed. In previous [...] Read more.
Worst performance in cognitive processing tasks shows larger relationships to general intelligence than mean or best performance. This so called Worst Performance Rule (WPR) is of major theoretical interest for the field of intelligence research, especially for research on mental speed. In previous research, the increases in correlations between task performance and general intelligence from best to worst performance were mostly described and not tested statistically. We conceptualized the WPR as moderation, since the magnitude of the relation between general intelligence and performance in a cognitive processing task depends on the performance band or percentile of performance. On the one hand, this approach allows testing the WPR for statistical significance and on the other hand, it may simplify the investigation of possible constructs that may influence the WPR. The application of two possible implementations of this approach is shown and compared to results of a traditional worst performance analysis. The results mostly replicate the WPR. Beyond that, a comparison of results on the level of unstandardized relationships (e.g., covariances or unstandardized regression weights) to results on the level of standardized relationships (i.e., correlations) indicates that increases in the inter-individual standard deviation from best to worst performance may play a crucial role for the WPR. Altogether, conceptualizing the WPR as moderation provides a new and straightforward way to conduct Worst Performance Analysis and may help to incorporate the WPR more prominently into empirical practice of intelligence research. Full article
(This article belongs to the Special Issue Mental Speed and Response Times in Cognitive Tests)
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Open AccessArticle
Predicting Fluid Intelligence by Components of Reaction Time Distributions from Simple Choice Reaction Time Tasks
J. Intell. 2016, 4(3), 8; https://doi.org/10.3390/jintelligence4030008 - 18 Jul 2016
Cited by 6 | Viewed by 4994
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Mental Speed and Response Times in Cognitive Tests)
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Open AccessArticle
Trait Characteristics of Diffusion Model Parameters
J. Intell. 2016, 4(3), 7; https://doi.org/10.3390/jintelligence4030007 - 18 Jul 2016
Cited by 10 | Viewed by 4764
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Mental Speed and Response Times in Cognitive Tests)
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