Evaluating evidence in linked crimes with multiple offenders
In de Zoete et al. (2015) a framework for the evaluation of evidence when an individual is a suspect of two separate offenses (based on Evett et al., 2006) is implemented using a Bayesian network. Here, we extend this to situations with multiple offenders. When we have multiple offenders, new questions arise: (1) Can we distinguish between the offenders, even if we do not know their identity? (2) Do we know that certain pieces of evidence originate from the same person? (3) Do we know the number of offenders? With the aid of a mock case example, we show that such subtle differences between situations can lead to substantially different conclusions in terms of posterior probabilities of a certain suspect being one of the offenders in a particular crime.
Source: Science and Justice - Category: Forensic Medicine Authors: Jacob de Zoete, Marjan Sjerps, Ronald Meester Tags: Emerging researcher article Source Type: research
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