Literature DB >> 27181589

A guideline for the validation of likelihood ratio methods used for forensic evidence evaluation.

Didier Meuwly1, Daniel Ramos2, Rudolf Haraksim3.   

Abstract

This Guideline proposes a protocol for the validation of forensic evaluation methods at the source level, using the Likelihood Ratio framework as defined within the Bayes' inference model. In the context of the inference of identity of source, the Likelihood Ratio is used to evaluate the strength of the evidence for a trace specimen, e.g. a fingermark, and a reference specimen, e.g. a fingerprint, to originate from common or different sources. Some theoretical aspects of probabilities necessary for this Guideline were discussed prior to its elaboration, which started after a workshop of forensic researchers and practitioners involved in this topic. In the workshop, the following questions were addressed: "which aspects of a forensic evaluation scenario need to be validated?", "what is the role of the LR as part of a decision process?" and "how to deal with uncertainty in the LR calculation?". The questions: "what to validate?" focuses on the validation methods and criteria and "how to validate?" deals with the implementation of the validation protocol. Answers to these questions were deemed necessary with several objectives. First, concepts typical for validation standards [1], such as performance characteristics, performance metrics and validation criteria, will be adapted or applied by analogy to the LR framework. Second, a validation strategy will be defined. Third, validation methods will be described. Finally, a validation protocol and an example of validation report will be proposed, which can be applied to the forensic fields developing and validating LR methods for the evaluation of the strength of evidence at source level under the following propositions.
Copyright © 2016. Published by Elsevier B.V.

Keywords:  Accreditation; Automatic interpretation method; Method validation; Strength of evidence; Validation report

Year:  2016        PMID: 27181589     DOI: 10.1016/j.forsciint.2016.03.048

Source DB:  PubMed          Journal:  Forensic Sci Int        ISSN: 0379-0738            Impact factor:   2.395


  13 in total

1.  A response to "Likelihood ratio as weight of evidence: A closer look" by Lund and Iyer.

Authors:  Simone Gittelson; Charles E H Berger; Graham Jackson; Ian W Evett; Christophe Champod; Bernard Robertson; James M Curran; Duncan Taylor; Bruce S Weir; Michael D Coble; John S Buckleton
Journal:  Forensic Sci Int       Date:  2018-05-22       Impact factor: 2.395

Review 2.  Interpol review of fingermarks and other body impressions 2016-2019.

Authors:  Andy Bécue; Heidi Eldridge; Christophe Champod
Journal:  Forensic Sci Int       Date:  2020-03-17       Impact factor: 2.395

Review 3.  Implementation of algorithms in pattern & impression evidence: A responsible and practical roadmap.

Authors:  H Swofford; C Champod
Journal:  Forensic Sci Int       Date:  2021-02-18       Impact factor: 2.395

4.  Likelihood ratio data to report the validation of a forensic fingerprint evaluation method.

Authors:  Daniel Ramos; Rudolf Haraksim; Didier Meuwly
Journal:  Data Brief       Date:  2016-11-18

5.  Euclidean Distances as measures of speaker similarity including identical twin pairs: A forensic investigation using source and filter voice characteristics.

Authors:  Eugenia San Segundo; Athanasios Tsanas; Pedro Gómez-Vilda
Journal:  Forensic Sci Int       Date:  2016-11-17       Impact factor: 2.395

6.  Validation of two parent-reported autism spectrum disorders screening tools M-CHAT-R and SCQ in Bamako, Mali.

Authors:  Modibo Sangare; Hamza B Toure; Amadou Toure; Adama Karembe; Housseini Dolo; Yaya I Coulibaly; Modibo Kouyate; Kadiatou Traore; Seidina A Diakité; Souleymane Coulibaly; Arouna Togora; Cheick Oumar Guinto; Gordon A Awandare; Seydou Doumbia; Mahamadou Diakite; Daniel H Geschwind
Journal:  eNeurologicalSci       Date:  2019-03-11

Review 7.  Interpol review of glass and paint evidence 2016-2019.

Authors:  Jose Almirall; Tatiana Trejos; Katelyn Lambert
Journal:  Forensic Sci Int       Date:  2020-03-19       Impact factor: 2.395

8.  Objective evaluation of similarity scores derived by Evofinder® system for marks on bullets fired from Chinese Norinco QSZ-92 pistols.

Authors:  Feng Dong; Yabin Zhao; Yaping Luo; Weifang Zhang; Yuesong Li
Journal:  Forensic Sci Res       Date:  2019-09-09

9.  In the context of forensic casework, are there meaningful metrics of the degree of calibration?

Authors:  Geoffrey Stewart Morrison
Journal:  Forensic Sci Int Synerg       Date:  2021-06-12

Review 10.  Bayesian Hierarchical Random Effects Models in Forensic Science.

Authors:  Colin G G Aitken
Journal:  Front Genet       Date:  2018-04-16       Impact factor: 4.599

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