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

研究知觉和记忆的主要工具之一是接收器操作特征(ROC)，它是命中(靶标试验中的是反应)与假警报(非靶标试验中的是反应)的曲线图。研究人员通常声称，这些曲线的细节有助于洞察感兴趣的认知现象。然而，还不清楚ROC是否足够丰富，从而可以区分不同的过程。要探索的基本思路是，跨不同领域收集的ROC是否具有相同的模式，即都可以用共同的加工来解释，还是具有不同的模式，即可以支持丰富的加工理论。基于我们的观察，我们将开发灵活的、非参数的、无模型的ROC模式等价性测试。这些测试将使我们能够评估ROC是否可以用来对处理过程做出详细的推断。理解人类的记忆在教育、专业培训、保健服务，甚至在法律环境中都有许多实际后果。记忆研究人员提出了许多双过程模型来解释他们的结果，包括“记忆-知道”、“自动控制”和“无意识-意识”。不幸的是，这些模型的直接检验往往缺乏严密性，因为它们在验证性模式下使用了诸如ROC这样的统计检验。这个项目将让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.