title: A guideline for the validation of likelihood ratio methods used for forensic evidence evaluation.
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.
authors.affiliation: Netherlands Forensic Institute, Laan van Ypenburg 6, 2497GB The Hague, The Netherlands; University of Twente, Drienerlolaan 5, 7522NB Enschede, The Netherlands. Electronic address: d.meuwly@nfi.minvenj.nl.
authors.forename: Didier
authors.initials: D
authors.lastname: Meuwly
authors.affiliation: ATVS - Biometric Recognition Group, Escuela Politecnica Superior, Universidad Autonoma de Madrid, C/Francisco Tomas y Valiente 11, 28049 Madrid, Spain.
authors.forename: Daniel
authors.initials: D
authors.lastname: Ramos
authors.affiliation: LTS5 - Signal Processing Laboratory, École Polytechnique Fédérale de Lausanne, Faculty of Electrical Engineering, Station 11, CH-1015 Lausanne, Switzerland.
authors.forename: Rudolf
authors.initials: R
authors.lastname: Haraksim
keywords: Accreditation; Automatic interpretation method; Method validation; Strength of evidence; Validation report