Eyewitness Identification: A Bird’s-Eye View

How should the legal system and scholars evaluate lineup performance? To answer this important question, we develop a theoretical framework based on two popular evaluation methods in eyewitness research—receiver operating characteristic (ROC) analysis and expected utility analysis. This framework contains two key components. First, we present an investigator signal detection model, which illustrates that ROC analysis examines investigator performance rather than eyewitness performance. Investigators use eyewitness evidence to classify suspects’ guilt or innocence—and lineup ROC curves capture their operating characteristics under different decision criteria. Second, we discuss the connection between ROC and expected utility, which highlights the dynamic nature of investigator decision making. The expected utility of investigator classification decisions is influenced not only by the quality of eyewitness evidence but also by factors such as investigators’ decision criteria, prior evidence, and consequences of the decisions. As its parameters embrace police investigative practices throughout different stages, the expected utility approach provides a comprehensive framework for evaluating investigator performance. To effectively evaluate and improve lineup practices, researchers need to consider not just witnesses but also the role played by investigators.