Validating a multinomial processing tree model for measuring confidence in lineups using a post-response feedback manipulation

Confidence in lineup responses is important in research and practice. Here we introduce the lineup confidence model, an extension of the well-validated two-high threshold eyewitness identification model. The two-high threshold eyewitness identification model serves to measure four cognitive processes underlying lineup responses: culprit-presence detection, culprit-absence detection, biased suspect selection and guessing-based selection. The lineup confidence model additionally incorporates the measurement of confidence. To validate the lineup confidence model, we conducted an experiment with a large sample size (N = 1565) using post-response feedback as a manipulation of confidence. Confidence followed a predictable and psychologically plausible pattern: responses based on detection were more likely to result in high confidence than responses based on guessing, and responses based on biased suspect selection were also more likely to result in high confidence than responses based on guessing. Importantly, post-response feedback selectively influenced confidence while leaving the parameters for culprit-presence detection, culprit-absence detection, biased suspect selection and guessing-based selection unaffected. Confidence can thus be measured with the model without compromising the measurement of the other processes specified by the model. This successful validation indicates that the lineup confidence model may be useful for examining how lineup characteristics and external factors influence confidence as a function of the processes underlying lineup responses.