  In many jurisdictions, forensic evidence is presented in the form of
categorical statements by forensic experts. Several large-scale performance
studies have been performed that report error rates to elucidate the
uncertainty associated with such categorical statements. There is growing
scientific consensus that the likelihood ratio (LR) framework is the logically
correct form of presentation for forensic evidence evaluation. Yet, results
from the large-scale performance studies have not been cast in this framework.
  Here, I show how to straightforwardly calculate an LR for any given
categorical statement using data from the performance studies. This number
quantifies how much more we should believe the hypothesis of same source vs
different source, when provided a particular expert witness statement. LRs are
reported for categorical statements resulting from the analysis of latent
fingerprints, bloodstain patterns, handwriting, footwear and firearms. The
highest LR found for statements of identification was 376 (fingerprints), the
lowest found for statements of exclusion was 1/28 (handwriting).
  The LRs found may be more insightful for those used to this framework than
the various error rates reported previously. An additional advantage of using
the LR in this way is the relative simplicity; there are no decisions necessary
on what error rate to focus on or how to handle inconclusive statements. The
values found are closer to 1 than many would have expected. One possible
explanation for this mismatch is that we undervalue numerical LRs. Finally, a
note of caution: the LR values reported here come from a simple calculation
that does not do justice to the nuances of the large-scale studies and their
differences to casework, and should be treated as ball-park figures rather than
definitive statements on the evidential value of whole forensic scientific
fields.
