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The Worst Performance Rule or the Not-Best Performance Rule? Latent-Variable Analyses of Working Memory Capacity Mind-Wandering Propensity and Reaction Time

机译:最糟糕的绩效规则或不最好的性能规则?潜在变量分析工作记忆力思维疏松倾向和反应时间

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摘要

The worst performance rule (WPR) is a robust empirical finding reflecting that people’s worst task performance shows numerically stronger correlations with cognitive ability than their average or best performance. However, recent meta-analytic work has proposed this be renamed the “not-best performance” rule because mean and worst performance seem to predict cognitive ability to similar degrees, with both predicting ability better than best performance. We re-analyzed data from a previously published latent-variable study to test for worst vs. not-best performance across a variety of reaction time tasks in relation to two cognitive ability constructs: working memory capacity (WMC) and propensity for task-unrelated thought (TUT). Using two methods of assessing worst performance—ranked-binning and ex-Gaussian-modeling approaches—we found evidence for both the worst and not-best performance rules. WMC followed the not-best performance rule (correlating equivalently with mean and longest response times (RTs)) but TUT propensity followed the worst performance rule (correlating more strongly with longest RTs). Additionally, we created a mini-multiverse following different outlier exclusion rules to test the robustness of our findings; our findings remained stable across the different multiverse iterations. We provisionally conclude that the worst performance rule may only arise in relation to cognitive abilities closely linked to (failures of) sustained attention.
机译:最糟糕的性能规则(WPR)是一种强大的实证发现,反映了人们最糟糕的任务性能显示与认知能力的数字更强烈的相关性,而不是其平均值或最佳性能。然而,最近的元分析工作已经提出,这更名为“不最好的性能”规则,因为平均值和最差的性能似乎预测了相似程度的认知能力,这两个都是比最佳性能更好的能力。我们从先前发布的潜在变量研究重新分析数据,以测试与两个认知能力构建的各种反应时间任务相比的最差与最佳性能的测试:工作存储器容量(WMC)和任务无关的倾向思想(tut)。使用两种评估最糟糕的性能排名和ex-gaussian建模方法的方法 - 我们发现了最糟糕和最佳性能规则的证据。 WMC遵循不最好的性能规则(与平均值和最长的响应时间(RTS)相当地关联),但TUT倾向遵循最糟糕的性能规则(与最长RTS更强烈地相关)。此外,我们在不同的异常值排除规则之后创建了一个迷你多层次,以测试我们的研究结果的稳健性;我们的调查结果仍然稳定,在不同的多层迭代中仍然稳定。我们暂时得出结论,最糟糕的绩效规则可能只会与与(失败)持续关注紧密相关的认知能力。

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