Department of Psychology, University of California, San Diego, La Jolla, CA 92093-0109, USA.
J Exp Psychol Appl. 2012 Dec;18(4):361-76. doi: 10.1037/a0030609.
A police lineup presents a real-world signal-detection problem because there are two possible states of the world (the suspect is either innocent or guilty), some degree of information about the true state of the world is available (the eyewitness has some degree of memory for the perpetrator), and a decision is made (identifying the suspect or not). A similar state of affairs applies to diagnostic tests in medicine because, in a patient, the disease is either present or absent, a diagnostic test yields some degree of information about the true state of affairs, and a decision is made about the presence or absence of the disease. In medicine, receiver operating characteristic (ROC) analysis is the standard method for assessing diagnostic accuracy. By contrast, in the eyewitness memory literature, this powerful technique has never been used. Instead, researchers have attempted to assess the diagnostic performance of different lineup procedures using methods that cannot identify the better procedure (e.g., by computing a diagnosticity ratio). Here, we describe the basics of ROC analysis, explaining why it is needed and showing how to use it to measure the performance of different lineup procedures. To illustrate the unique advantages of this technique, we also report 3 ROC experiments that were designed to investigate the diagnostic accuracy of simultaneous versus sequential lineups. According to our findings, the sequential procedure appears to be inferior to the simultaneous procedure in discriminating between the presence versus absence of a guilty suspect in a lineup.
在警方列队辨认中存在一个现实的信号检测问题，因为世界上存在两种可能的状态（嫌疑人要么是无辜的，要么是有罪的），对真实状态有一定程度的了解（目击者对犯罪人有一定程度的记忆），并且需要做出一个决定（是否指认嫌疑人）。医学中的诊断测试也存在类似的情况，因为在患者中，疾病要么存在，要么不存在，诊断测试提供了关于真实情况的一定程度的信息，并且需要做出关于疾病存在或不存在的决定。在医学中，接收器操作特征 (ROC) 分析是评估诊断准确性的标准方法。相比之下，在目击者记忆文献中，这种强大的技术从未被使用过。相反，研究人员试图使用无法识别更好程序的方法（例如，计算诊断率）来评估不同的列队辨认程序的诊断性能。在这里，我们描述了 ROC 分析的基础知识，解释了为什么需要它，并展示了如何使用它来衡量不同列队辨认程序的性能。为了说明该技术的独特优势，我们还报告了 3 个 ROC 实验，旨在调查同时和顺序列队辨认在区分列队中是否存在有罪嫌疑人方面的诊断准确性。根据我们的发现，在区分列队中是否存在有罪嫌疑人方面，顺序程序似乎不如同时程序准确。
