Study title

This collection contains four spreadsheets with raw data from many experiments. The research involved collecting behavioural data online from human participants. In each experiment, participants were randomly assigned to a condition, watched a video of a target committing a mock crime, took part in a brief distractor task, attempted to identify the target out of a lineup, answered a validation question, and provided demographic information. There is a two-pronged, very real societal problem concerning identifications made by eyewitnesses: innocent suspects are mistakenly identified and charged with a crime they did not commit, or guilty suspects are not identified and free to commit more crimes. Decreasing the chances that innocent suspects are misidentified, unfortunately also decreases the chances that guilty suspects are identified; and likewise, increasing the chances that guilty suspects are identified also increases the chances that innocent suspects are identified. In other words, an eyewitness's accuracy is not just about choosing the right suspect; it is also about not misidentifying the wrong suspect. This teeter tottering is what eyewitness memory researchers have been grappling with for decades, and we aim to combat it. That may seem like a bold claim, but it is now possible because of the new method of analysis we recently introduced to the field of eyewitness memory. The method disentangles the concept of response bias (i.e., the inclination of an eyewitness to choose someone or not choose someone from an identification parade) from discriminability (i.e., the ability to discriminate an innocent suspect from a guilty suspect). While the method is new to eyewitness memory researchers, the method is tried-and-true for medical diagnosticians who routinely use it to test whether one diagnostic procedure is better able to discriminate a disease state from a non-disease state, for example. Eyewitness memory researchers are faced with the same conceptual...