Value of evidence in the rare type match problem: Common source versus specific source

In the so-called rare type match problem, the discrete characteristics of a crime stain have not been observed in the set of background material. To assess the strength of evidence, two competing statistical hypotheses need to be considered. The formulation of the hypotheses depends on whichidentification of source question is of interest (Ommen, 2017, Approximate statistical solutions tothe forensic identification of source problem. (Phd thesis). South Dakota State University). Assuming that the evidence has been generated according to the beta-binomial model, two quantifications of the value of evidence can be found in the literature, but no clear indication is given when to use either of these. When the likelihood ratio is used to quantify the value of evidence, an estimateis needed for the frequency of the discrete characteristics. The central discussion is about whether or not one of the traces needs to be added to the background material when determining this estimate. In this article it is shown, using fully Bayesian methods, that one of the values of evidence from the literature corresponds to the so-called 'identification of common source' problem and the other to the 'identification of specific source' problem (Ommen, 2017, Approximate statistical solutions to the forensic identification of source problem. (Phd thesis). South Dakota State University). This means that the question whether or not one of the traces needs to be added to the background material reduces to the question whether a common source or specific source problem is under consideration. The distinction between the two values is especially important for the rare type match problem, since the values of evidence differ most in this situation. </p

Uncertainty and LR: to integrate or not to integrate, that’s the question

Taroni et al. (2016) discuss the controversial issue of parameter uncertainty in the context of forensic evidence evaluation. Although we share with the authors the main idea that the likelihood ratio (LR) framework is the best method for evaluating forensic evidence, we have a different view on this issue. The core question is: does it make sense to consider the uncertainty attached to a calculated value of the LR, and consequently, should we report a single value for the LR or in addition address its uncertainty? Taroni et al. (2016) argue for reporting a single value based on a ‘full-Bayesian’ approach, and accuse anyone who considers the uncertainty of an LR of ‘misconception of basic principles’ and ‘abuse of language’. However, their arguments presented as facts or logic are in fact choices or opinions. Furthermore, reporting a single number for the LR deprives the legal justice system of essential information needed to assess the reliability of the evidence. Therefore, we argue that forensic scientists should not only report an LR value, but also address its uncertainty and we explain why this is not a misconception or abuse of language

Pistol bullet deflection through soft tissue simulants.

Trajectory deflections of pistol bullets from four different firearms, fired through soft tissue simulants under two different incidence and exit angles were studied. The data from this study can be used in reconstructions of shooting incidents where human soft tissues (not bones) were perforated with pistol bullets and assumptions must be made about bullet deflection in order to correctly reconstruct trajectories. The results demonstrate that deflection was influenced by the length of the "wound channel" through the simulants. In short, deflection was small to virtually absent with 5 and 10cm channel lengths. With channel lengths of 15, 20 and 25cm, there was a clear increase in deflection and/or a more erratic deflection behaviour with most shots. The data also suggest an influence of the angle of incidence and/or exit on both the direction and the magnitude of the deflection

Uncertainty and LR: to integrate or not to integrate, that’s the question

Taroni et al. (2016) discuss the controversial issue of parameter uncertainty in the context of forensic evidence evaluation. Although we share with the authors the main idea that the likelihood ratio (LR) framework is the best method for evaluating forensic evidence, we have a different view on this issue. The core question is: does it make sense to consider the uncertainty attached to a calculated value of the LR, and consequently, should we report a single value for the LR or in addition address its uncertainty? Taroni et al. (2016) argue for reporting a single value based on a ‘full-Bayesian’ approach, and accuse anyone who considers the uncertainty of an LR of ‘misconception of basic principles’ and ‘abuse of language’. However, their arguments presented as facts or logic are in fact choices or opinions. Furthermore, reporting a single number for the LR deprives the legal justice system of essential information needed to assess the reliability of the evidence. Therefore, we argue that forensic scientists should not only report an LR value, but also address its uncertainty and we explain why this is not a misconception or abuse of language

Value of evidence in the rare type match problem: Common source versus specific source

In the so-called rare type match problem, the discrete characteristics of a crime stain have not been observed in the set of background material. To assess the strength of evidence, two competing statistical hypotheses need to be considered. The formulation of the hypotheses depends on whichidentification of source question is of interest (Ommen, 2017, Approximate statistical solutions tothe forensic identification of source problem. (Phd thesis). South Dakota State University). Assuming that the evidence has been generated according to the beta-binomial model, two quantifications of the value of evidence can be found in the literature, but no clear indication is given when to use either of these. When the likelihood ratio is used to quantify the value of evidence, an estimateis needed for the frequency of the discrete characteristics. The central discussion is about whether or not one of the traces needs to be added to the background material when determining this estimate. In this article it is shown, using fully Bayesian methods, that one of the values of evidence from the literature corresponds to the so-called 'identification of common source' problem and the other to the 'identification of specific source' problem (Ommen, 2017, Approximate statistical solutions to the forensic identification of source problem. (Phd thesis). South Dakota State University). This means that the question whether or not one of the traces needs to be added to the background material reduces to the question whether a common source or specific source problem is under consideration. The distinction between the two values is especially important for the rare type match problem, since the values of evidence differ most in this situation. Delft Institute of Applied Mathematic