In recent years, the forensic community has pushed to increase the scienti c basis of forensic evidence, which has included pro ciency testing for ngerprint analysts. We use pro ciency testing data collected by Collaborative Testing Services in which 431 ngerprint analysts were asked to identify the source of latent prints. The data were analyzed using a Rasch model with a Bayesian estimation approach. Although these data provide valuable information about the relative ability of the examiners and the relative di culty of the questions, it does not necessarily extrapolate onto general performance of examiners or di culty in casework, which we show through sensitivity analysis and simulation. We show that a Bayesian Item Response Theory analysis provides a deeper understanding of analysts’ ability and question di culty than other forms of analysis. A large-scale adoption of Item Response Theory in this area would provide both more precise estimates of pro ciency and quantitative evidence for the relative di culty of di erent questions.

中文翻译：

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贝叶斯项目反应理论对指纹检查员的能力测试1

近年来，法医界一直在努力增加法医证据的科学基础，其中包括对指纹分析师的能力测试。我们使用 Collaborative Testing Services 收集的能力测试数据，其中 431 名指纹分析师被要求确定潜在指纹的来源。使用具有贝叶斯估计方法的 Rasch 模型分析数据。虽然这些数据提供了关于考官的相对能力和问题的相对难度的有价值的信息，但它不一定能推断出考官的一般表现或案例工作的难度，我们通过敏感性分析和模拟来展示。我们表明，与其他形式的分析相比，贝叶斯项目反应理论分析可以更深入地了解分析师的能力和问题难度。