From data to a validated score-based LR system: A practitioner’s guide
Anna Jeannette Leegwater, Peter Vergeer, Ivo Alberink, L.V. van der Ham, Judith van de Wetering, Rachid el Harchaoui, Wauter Bosma, Rolf J.F. Ypma, Marjan Sjerps
Abstract
Likelihood ratios (LRs) are a useful measure of evidential strength. In forensic casework consisting of a flow of cases with essentially the same question and the same analysis method, it is feasible to construct an 'LR system', that is, an automated procedure that has the observations as input and an LR as output. This paper is aimed at practitioners interested in building their own LR systems. It gives an overview of the different steps needed to get to a validated LR system from data. The paper is accompanied by a notebook that illustrates each step with an example using glass data. The notebook introduces open-source software in Python constructed by NFI (Netherlands Forensic Institute) data scientists and statisticians.