Can Behavioral Data Underlying Receiver Operating Characteristic (ROC) Analysis Support Complex Theories of Perception and Memory?

感知和记忆研究的主要工具之一是受试者操作特征（ROC），它是命中（目标试验的“是”响应）与假警报（非目标试验的“是”响应）的图。研究人员通常声称，这些曲线的细节提供了对感兴趣的认知现象的洞察。然而，目前尚不清楚ROC是否足够丰富，以允许过程的差异化。需要探讨的基本思想是，跨不同领域收集的ROCs是否具有相同的模式，即都可以用共同的加工来解释，或者具有不同的模式，即可以支持丰富的加工理论。根据我们的观察，我们将开发灵活的，非参数的，无模型的ROC模式等效性测试。这些测试将使我们能够评估ROCs是否可以用于对处理过程进行详细的推断。理解人类记忆在教育、专业培训、医疗服务甚至在法律的环境中都有许多实际的影响。 记忆研究者提出了许多双过程模型来解释他们的结果，包括“记住-知道”、“自动控制”和“无意识-有意识”。不幸的是，这些模型的直接测试往往缺乏严谨性，因为他们使用了统计测试，如ROC验证模式。该项目将使感知和记忆研究人员了解如何以更有原则的方式使用ROC。

One of the primary tools in the investigation of perception and memory is the Receiver Operating Characteristic (ROC), which is a plot of hits ('yes' responses on target trials) vs. false alarms ('yes' responses on non-target trials). Researchers commonly claim that the details of these curves provide insight into cognitive phenomena of interest. It is not clear, however, that ROCs are sufficiently rich so as to allow differentiation of processes. The basic idea to be explored is whether ROCs collected across disparate domains have the same pattern, that is, can all be explained by common processing, or have different patterns, that is, can support rich theories of processing. Based on our observations, we will develop flexible, nonparametric, model-free tests of ROC pattern equivalence. These tests will allow us to assess whether ROCs can be used to make detailed inferences about processing.Understanding human memory has many practical consequences in education, professional training, health delivery, and even in legal settings. Memory researchers have posited many two-process models to account for their results, including 'remember-know', 'automatic-controlled', and 'unconscious-conscious'. Unfortunately, direct tests of these models have often lacked rigor, because they have used statistical tests such as ROCs in a confirmatory mode. This project will allow perception and memory researchers to understand how to use ROCs in a more principled way.