title: Towards source level evaluation of the evidential value of fibre examinations.
abstract: This paper aims to provide the first steps towards a numerical source level evaluation of fibre evidence. For that purpose, likelihood ratio equations are derived for four generic scenarios, in which the source frequency, the number of references and trace types investigated, and the number of matches vary. Previous experimental studies into the evaluation of fibre evidence are reviewed and we demonstrate how the results of these studies, as well as other data, can be used to evaluate the derived equations for the four scenarios. Evaluation is not straightforward and requires a number of assumptions. This is mainly because the relevant population under consideration in a specific case cannot be sufficiently evaluated. In addition, the subjective match-criterion in current forensic fibre examinations makes it impossible to implement a good evaluation of the within-variation of samples. As a result, the discrimination power, currently calculated for discrimination studies, is only valid for samples with negligible heterogeneity. We conclude that reporting a numerical evidential value for forensic fibre examinations is not yet feasible as the data are available for only a few types of fibres and cannot be used without several assumptions. We propose a number of developments that are required to improve the accuracy and numerical analysis.
authors.affiliation: Netherlands Forensic Institute, P.O. Box 24044, 2490AA The Hague, the Netherlands.
authors.forename: Cees
authors.initials: C
authors.lastname: Vooijs
authors.affiliation: Netherlands Forensic Institute, P.O. Box 24044, 2490AA The Hague, the Netherlands.
authors.forename: Peter
authors.initials: P
authors.lastname: Vergeer
authors.affiliation: Netherlands Forensic Institute, P.O. Box 24044, 2490AA The Hague, the Netherlands. Electronic address: jawee@nfi.minvenj.nl.
authors.forename: Jaap
authors.initials: J
authors.lastname: van der Weerd
keywords: Discrimination power; Discrimination study; Fiber evidence; Likelihood ratio LR; Match; Numerical evaluation; Population study