Statistical Support for Conclusions in Fingerprint Examinations

Neumann, Cédric; Hendricks, Jessie; Ausdemore, Madeline

doi:10.1201/9780367527709-13

Cited by 6 publications

(3 citation statements)

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“…One encounters two kinds of LR assessments in the literature—feature‐based LR s and score‐based LR s. Several authors have pointed out the deficiencies of score‐based LR s and have questioned their suitability for use in forensic settings (Bolck et al., 2015; Neumann, 2020; Neumann & Ausdemore, 2020; Neumann et al., 2020). In any case, our procedure applies equally well for exploring the reliability of either approach.…”

Section: Introductionmentioning

confidence: 99%

Testing for Calibration Discrepancy of Reported Likelihood Ratios in Forensic Science

Hannig¹,

Iyer

2021

Journal of the Royal Statistical Society Series A: Statistics in Society

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Section: Introductionmentioning

confidence: 99%

Testing for Calibration Discrepancy of Reported Likelihood Ratios in Forensic Science

Hannig¹,

Iyer

2021

Journal of the Royal Statistical Society Series A: Statistics in Society

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“…An extended discussion of limitations of score-based likelihood ratios will be the subject of a second paper and is summarized inNeumann et al (2019).…”

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“…The general convergence between the FRStat ratio and the specific source likelihood ratio (Ommen et al, 2017(Ommen et al, , 2018 has been studied by Neumann et al (2019). Some results obtained using a toy example are reproduced in Figure 4.…”

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confidence: 99%

Defence against the modern arts: the curse of statistics: Part I—FRStat

Neumann

2020

Law, Probability and Risk

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For several decades, legal and scientific scholars have argued that conclusions from forensic examinations should be supported by statistical data and reported within a probabilistic framework. Multiple models have been proposed to quantify the probative value of forensic evidence. Unfortunately, several of these models rely on ad-hoc strategies that are not scientifically sound. The opacity of the technical jargon that is used to present these models and their results and the complexity of the techniques involved make it very difficult for the untrained user to separate the wheat from the chaff. This series of paper is intended to help forensic scientists and lawyers recognise issues in tools proposed to interpret the results of forensic examinations. This paper focuses on the tool proposed by the Latent Print Branch of the U.S. Defense Forensic Science Center (DFSC) and called FRStat. In this paper, I explore the compatibility of the results outputted by FRStat with the language used by the DFCS to report the conclusions of their fingerprint examinations, as well as the appropriateness of the statistical modelling underpinning the tool and the validation of its performance.

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Characterization of fracture match associations with automated image processing

Spaulding

Picconatto

2023

Forensic Science International

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Statistical Support for Conclusions in Fingerprint Examinations

Cited by 6 publications

References 1 publication

Testing for Calibration Discrepancy of Reported Likelihood Ratios in Forensic Science

Testing for Calibration Discrepancy of Reported Likelihood Ratios in Forensic Science

Defence against the modern arts: the curse of statistics: Part I—FRStat

Characterization of fracture match associations with automated image processing

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