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.

翻译：在许多司法管辖区，法医证据以专家分类陈述的形式呈现。已有几项大规模绩效研究报告了错误率，以阐明此类分类陈述所伴随的不确定性。科学界日益形成共识，即似然比框架是法医证据评估在逻辑上正确的呈现形式。然而，这些大规模绩效研究的结果尚未被纳入该框架。本文展示了如何利用绩效研究数据，直接计算任何给定分类陈述的似然比。该数值量化了在获得特定专家证人陈述时，我们应更相信"同一来源"假说而非"不同来源"假说的程度。本研究针对潜指纹、血迹形态、笔迹、鞋印和枪弹痕迹分析所产生的分类陈述报告了似然比。识别陈述的最高似然比为376（指纹），排除陈述的最低似然比为1/28（笔迹）。对于熟悉该框架的研究者而言，这些似然比值可能比先前报告的各种错误率更具洞察力。此外，以这种方式使用似然比的另一优势在于其相对简易性：无需决定应关注哪种错误率或如何处理无结论性陈述。所得数值比许多人预期的更接近1。这一差异的可能解释是我们低估了数值似然比的价值。最后需注意的是：本文报告的似然比来自简单计算，未能充分反映大规模研究的细微差别及其与案例工作的差异，应视为近似值而非对整个法医科学领域证据价值的确定性论断。