What latent variable underlies confidence in lineup rejections?

Abstract

When a face is positively identified from a multi-person photo lineup, it is presumably the face that generates the strongest memory signal. In addition, confidence in a positive identification is presumably determined by the strength of the memory signal associated with that face. However, when no face generates a strong enough memory signal to be identified, the entire set of faces in the lineup is collectively rejected. What latent variable underlies confidence in a lineup rejection? One possibility is that the face that generates the strongest memory signal still determines confidence (i.e., the weaker that memory signal is, the more confidently the lineup is rejected). Another possibility is that confidence in a lineup rejection is determined by the average strength of the memory signals generated by the faces in the lineup (i.e., the weaker that average memory signal is, the more confidently the lineup is rejected). The reliance on an average signal has been proposed as a possible explanation for why the confidence-accuracy for lineup rejections tends to be weak. Here, we modified two existing signal-detection-based lineup models (the Independent Observations model and the Ensemble model) and fit them to multiple lineup datasets to investigate which decision variable underlies confidence in lineup rejections. Both models agree that confidence in a lineup rejection is based on the strongest memory signal in the lineup, not on the average signal. These model fits also revealed for the first time that the memory signals in a lineup are correlated, as they theoretically should be.