  Measures of face-identification proficiency are essential to ensure accurate
and consistent performance by professional forensic face examiners and others
who perform face-identification tasks in applied scenarios. Current proficiency
tests rely on static sets of stimulus items, and so, cannot be administered
validly to the same individual multiple times. To create a proficiency test, a
large number of items of "known" difficulty must be assembled. Multiple tests
of equal difficulty can be constructed then using subsets of items. We
introduce the Triad Identity Matching (TIM) test and evaluate it using Item
Response Theory (IRT). Participants view face-image "triads" (N=225) (two
images of one identity, one image of a different identity) and select the
different identity. In Experiment 1, university students (N=197) showed
wide-ranging accuracy on the TIM test, and IRT modeling demonstrated that the
TIM items span various difficulty levels. In Experiment 2, we used IRT-based
item metrics to partition the test into subsets of specific difficulties.
Simulations showed that subsets of the TIM items yielded reliable estimates of
subject ability. In Experiments 3a and 3b, we found that the student-derived
IRT model reliably evaluated the ability of non-student participants and that
ability generalized across different test sessions. In Experiment 3c, we show
that TIM test performance correlates with other common face-recognition tests.
In summary, the TIM test provides a starting point for developing a framework
that is flexible and calibrated to measure proficiency across various ability
levels (e.g., professionals or populations with face-processing deficits).
