University of California, Irvine, CA, USA.
University of Missouri, Columbia, MO, USA.
Psychon Bull Rev. 2019 Apr;26(2):452-467. doi: 10.3758/s13423-018-1558-y.
In modern individual-difference studies, researchers often correlate performance on various tasks to uncover common latent processes. Yet, in some sense, the results have been disappointing as correlations among tasks that seemingly have processes in common are often low. A pressing question then is whether these attenuated correlations reflect statistical considerations, such as a lack of individual variability on tasks, or substantive considerations, such as that inhibition in different tasks is not a unified concept. One problem in addressing this question is that researchers aggregate performance across trials to tally individual-by-task scores. It is tempting to think that aggregation is fine and that everything comes out in the wash. But as shown here, this aggregation may greatly attenuate measures of effect size and correlation. We propose an alternative analysis of task performance that is based on accounting for trial-by-trial variability along with the covariation of individuals' performance across tasks. The implementation is through common hierarchical models, and this treatment rescues classical concepts of effect size, reliability, and correlation for studying individual differences with experimental tasks. Using recent data from Hedge et al. Behavioral Research Methods, 50(3), 1166-1186, 2018 we show that there is Bayes-factor support for a lack of correlation between the Stroop and flanker task. This support for a lack of correlation indicates a psychologically relevant result-Stroop and flanker inhibition are seemingly unrelated, contradicting unified concepts of inhibition.
在现代个体差异研究中，研究人员经常将各种任务的表现相关联，以揭示共同的潜在过程。然而，从某种意义上说，结果令人失望，因为看似具有共同过程的任务之间的相关性通常较低。那么，一个紧迫的问题是，这些减弱的相关性是否反映了统计考虑因素，例如任务上缺乏个体可变性，或者实质性考虑因素，例如不同任务中的抑制不是一个统一的概念。解决这个问题的一个问题是，研究人员将表现汇总到各个试验中，以汇总个体的任务得分。人们很容易认为聚合是好的，一切都会被清除。但是，如这里所示，这种聚合可能会大大降低效应大小和相关性的度量。我们提出了一种替代的任务表现分析方法，该方法基于考虑到试验到试验的变异性以及个体在任务之间的表现协变。实现方法是通过常见的层次模型，这种处理方法为研究具有实验任务的个体差异提供了经典的效应大小、可靠性和相关性概念。我们使用 Hedge 等人的最新数据。行为研究方法，50(3)，1166-1186，2018 我们表明，Stroop 和侧翼任务之间缺乏相关性存在贝叶斯因子支持。这种缺乏相关性的支持表明了一个心理相关的结果——Stroop 和侧翼抑制似乎是不相关的，这与抑制的统一概念相矛盾。
