Guiding proposition setting in forensic DNA interpretation. Issue 5 (September 2022)

• Record Type: Journal Article
• Authors: Buckleton, John; Kalafut, Tim; Curran, James
• Is Part Of: Science & justice. Volume 62:Issue 5(2022)
• Page Start: 540
• Page End: 546
• Publication Date: 2022-09
• Subjects: Forensic DNA mixture interpretation -- Probabilistic genotyping -- Conditioning; Forensic sciences -- Periodicals; Criminal investigation -- Periodicals; Forensic Medicine -- Periodicals; Jurisprudence -- Periodicals; Criminalistique -- Périodiques; Enquêtes criminelles -- Périodiques; Criminal investigation; Forensic sciences; Electronic journals; Periodicals; 363.2505
• DOI: 10.1016/j.scijus.2022.08.002
• Languages: English
• ISSNs: 1355-0306

Abstract

Highlights: We discuss three situations where there are divided positions on whether to condition. For items requiring two POI for H p assume the stronger supported POI. Slooten states: take the highest LR under H p and divide by the highest LR under H a . Slooten's principle works for multiple POI and other potentially assumed contributors. Note that not to assume a contributor assumes that they were not a contributor. Abstract: There is a general reluctance to use conditioning profiles when forming propositions for cases where the evidence is a DNA mixture. However, the use of conditioning profiles improves the ability to differentiate true from false donors. There are at least four situations where this decision making is at its most difficult. These are: The unassociated item scenario, the two POI scenario, the uncertain background information scenario, and the one party assertion scenario. Rigorous mathematical treatment, given by Slooten and others, appears to offer strong guidance for these situations. This treatment assumes that the prior probabilities for conditioning, or not conditioning, on any individual are not extreme. It is when these prior probabilities appear ambiguous that the decision to condition or not can appear to be problematic. This is often the situation found in casework. In this paper we attempt to show that such situations may benefit most from following such guidance. A lower bound on the Bayes factor can be obtained by finding the highest LR that includes the POI and dividing by the highest LR that does not include the POI. These two highest LRs may be found with and without the disputed conditioning profile. The resultant lower bound is on the BF for the inclusion of the POI without directly assuming the disputed conditioning profile. Adopting this approach would both minimize adventitious inclusions and approximate an exhaustive set of propositions.