Although individual-difference studies have been invaluable in several domains of psychology, there has been less success in cognitive domains using experimental tasks. The problem is often called one of reliability: Individual differences in cognitive tasks, especially cognitive-control tasks, seem too unreliable. In this article, we use the language of hierarchical models to define a novel reliability measure—a signal-to-noise ratio—that reflects the nature of tasks alone without recourse to sample sizes. Signal-to-noise reliability may be used to plan appropriately powered studies as well as understand the cause of low correlations across tasks should they occur. Although signal-to-noise reliability is motivated by hierarchical models, it may be estimated from a simple calculation using straightforward summary statistics.

中文翻译：

---

用于规划和解释认知能力个体差异研究的分层模型见解

尽管个体差异研究在心理学的多个领域中具有无价的价值，但在认知领域中使用实验任务的成功却较少。这一问题通常被称为可靠性问题：认知任务中的个体差异，尤其是认知控制任务，似乎太不可靠。在本文中，我们使用分层模型的语言来定义一种新颖的可靠性度量（信噪比），它仅反映任务的性质，而无需依赖样本大小。信噪比可靠性可用于规划适当的动力研究，以及了解任务之间相关性较低的原因（如果发生）。尽管信噪比可靠性是由分层模型驱动的，但它可以通过使用简单的汇总统计的简单计算来估计。