A review of the worst performance rule: Evidence, theory, and alternative hypotheses

Coyle, Thomas R.

doi:10.1016/s0160-2896(03)00054-0

Cited by 98 publications

(126 citation statements)

References 22 publications

Supporting

Mentioning

111

Contrasting

Unclassified

Order By: Relevance

“…The RT × intelligence relation obeys the so called Worst Performance Rule, which states that the worst (slowest) RT trials performed by an individual, i.e. the trials most likely to be affected by attentional lapses, show the strongest association to intelligence (Coyle 2003). As noted, more complex RT tasks show a stronger correlation with intelligence (Jensen 1998); typically, a more complex decision space is also associated with a higher executive load (Rowe et al 2000).…”

Section: Introductionmentioning

confidence: 93%

“…Attentional systems show strong relations to intelligence (Schweizer and Moosbrugger 2004;Schweizer et al 2005). There is also strong evidence that CRT performance depends on attention: CRT shows interference under dual task (Telford 1931;Pashler 1994), involves fronto-striatal networks of importance for top-down control (D'Esposito et al 2000;Schluter et al 2001;Gilbert et al 2006), and its relations to intelligence follow the Worst Performance Rule (Coyle 2003).…”

Section: Unique Contributions Of Timing Variables To Intelligencementioning

confidence: 99%

See 1 more Smart Citation

Intelligence and temporal accuracy of behaviour: unique and shared associations with reaction time and motor timing

2011

View full text Add to dashboard Cite

Intelligence and temporal accuracy of behavior: unique and shared associations with reaction time and motor timing Experimental Brain Research, 2011, Vol. 214, Issue 2, p. 175 -183 doi 10.1007/s00221-011-2817 Access to the published version may require subscription. Published with permission from: Springer AbstractIntelligence is associated with accuracy in a wide range of timing tasks. One source of such associations is likely to be individual differences in top-down control, e.g. sustained attention, that influence performance in both temporal tasks and other cognitively controlled behaviors.In addition, we have studied relations between intelligence and a simple rhythmic motor task, isochronous serial interval production (ISIP), and found a substantial component of that relation, which is independent of fluctuations in top-down control. The main purpose of the present study was to investigate whether such bottom-up mechanisms are involved also in the relation between intelligence and reaction time (RT) tasks. We thus investigated if common variance between the ISIP and RT tasks underlies their respective associations with intelligence. 112 participants performed a simple RT task, a choice RT task and the ISIP task.Intelligence was assessed with the Raven SPM Plus. The analysed timing variables included mean and variability in the RT tasks and two variance components in the ISIP task. As predicted, RT and ISIP variables were associated with intelligence. The timing variables were positively intercorrelated and a principal component analysis revealed a substantial first principal component that was strongly related to all timing variables, and positively correlated with intelligence. Furthermore, a commonality analysis demonstrated that the relations between intelligence and the timing variables involved a commonality between the timing variables as well as unique contributions from choice RT and ISIP. We discuss possible implications of these findings, and argue that they support our main hypothesis, i.e. that relations between intelligence and RT tasks have a bottom-up component.

show abstract

Section: Introductionmentioning

confidence: 93%

Section: Unique Contributions Of Timing Variables To Intelligencementioning

confidence: 99%

Intelligence and temporal accuracy of behaviour: unique and shared associations with reaction time and motor timing

2011

View full text Add to dashboard Cite

show abstract

“…There already may be a hint of this in the "worst performance rule (WPR)" [123], which is based on a finding that the average response time from one's slowest responses (or, say, the 90th percentile of response times for an individual) is more highly correlated with cognitive ability than is one's mean response time across all responses [124]. The WPR could result from the comparison between uninformative rapid guessing responses vs. informative full processing responses [125].…”

Section: Fast Vs Slow Responding = Fast Vs Slow Thinking?mentioning

confidence: 99%

Use of Response Time for Measuring Cognitive Ability

Kyllonen

2016

J. Intell.

109

View full text Add to dashboard Cite

Abstract:The purpose of this paper is to review some of the key literature on response time as it has played a role in cognitive ability measurement, providing a historical perspective as well as covering current research. We discuss the speed-level distinction, dimensions of speed and level in cognitive abilities frameworks, speed-accuracy tradeoff, approaches to addressing speed-accuracy tradeoff, analysis methods, particularly item response theory-based, response time models from cognitive psychology (ex-Gaussian function, and the diffusion model), and other uses of response time in testing besides ability measurement. We discuss several new methods that can be used to provide greater insight into the speed and level aspects of cognitive ability and speed-accuracy tradeoff decisions. These include item-level time limits, the use of feedback (e.g., CUSUMs), explicit scoring rules that combine speed and accuracy information (e.g., count down timing), and cognitive psychology models. We also review some of the key psychometric advances in modeling speed and level, which combine speed and ability measurement, address speed-accuracy tradeoff, allow for distinctions between response times on items responded to correctly and incorrectly, and integrate psychometrics with information-processing modeling. We suggest that the application of these models and tools is likely to advance both the science and measurement of human abilities for theory and applications.

show abstract

“…Individual differences in IIV seem more predictive of other individual differences. This could also be because extreme responses (i.e., a more skewed distribution) better distinguishes individuals from one another; the worst-performance rule, according to which intelligence (g) is predicted better by worse-performance than by betterperformance trials, goes in the same direction (Coyle, 2003;see also Fernandez, Fagot, Dirk, & de Ribaupierre, 2014). This does not yet explain IIV, but does demonstrate that it should no longer be neglected.…”

Section: Intraindividual Variabilitymentioning

confidence: 99%

Working memory and intraindividual variability in processing speed: A lifespan developmental and individual-differences study

et al. 2014

View full text Add to dashboard Cite

Working memory (WM) and intraindividual variability (IIV) in processing speed are both hypothesized to reflect general attentional processes. In the present study, we aimed at exploring the relationship between WM capacity and IIV in reaction times (RTs) and its possible variation with development across the lifespan. Two WM tasks and six RT tasks of varying complexity were analyzed in a sample of 539 participants, consisting of five age groups: two groups of children (9-10 and 11-12 years of age), one group of young adults, and two groups of older adults (59-69 and 70-89 years of age). Two approaches were adopted. First, low-span and high-span individuals were identified, and analyses of variance were conducted comparing these two groups within each age group and for each RT task. The results consistently showed a span effect in the youngest children and oldest adults: High-span individuals were significantly faster and less variable than low-span individuals. In contrast, in young adults no difference was observed between high-and lowspan individuals, whether in terms of their means or IIV. Second, multivariate analyses were conducted on the entire set of tasks, to determine whether IIV in RTs brought different information than the mean RT. The results showed that, although very strongly correlated, the mean and IIV in speed should be kept separate in terms of how they account for individual differences in WM. Overall, our results support the assumption of a link between WM capacity and IIV in RT, more strongly so in childhood and older adulthood.Keywords Aging . Development . Individual differences . Reaction time analyses/methods . Working memory . Intraindividual variabilityThe objective of the present article is to address the issue of the relationship between working memory (WM) capacity and within-task intraindividual variability (IIV) in reaction time (RT) tasks, investigating whether this relationship might vary across the lifespan. In this introduction, we will briefly present our approach to WM-in conformity with the demand of the editor of this special issue-and then discuss why a potential relationship can be hypothesized between WM and IIV and whether individual differences in WM could be related to IIV.As a number of researchers interested in developmental and/ or individual differences in WM, we consider the performance in WM tasks to be determined by a set of underlying attentional processes. These processes, such as the activation and inhibition of relevant informational units, are considered to become more efficient with age, accounting for part of cognitive development in children, and to vary in efficacy across individuals. We consider WM to be an index of what has frequently, and rather loosely, been labeled general resources. WM capacity, while remaining severely limited, increases with age both because of an increase in neurobiological mechanisms and because the use of resources becomes more efficient with experience. There is here a major point of departure between cognitive ex...

show abstract

A review of the worst performance rule: Evidence, theory, and alternative hypotheses

Cited by 98 publications

References 22 publications

Intelligence and temporal accuracy of behaviour: unique and shared associations with reaction time and motor timing

Intelligence and temporal accuracy of behaviour: unique and shared associations with reaction time and motor timing

Use of Response Time for Measuring Cognitive Ability

Working memory and intraindividual variability in processing speed: A lifespan developmental and individual-differences study

Contact Info

Product

Resources

About