An Investigation into Compound Likelihood Ratios for Forensic DNA Mixtures

• NCJ Number: 307020
• Journal: Genes Volume: 14 Issue: 3 Dated: March 2023 Pages: 714
• Author(s): Richard Wivell; Hannah Kelly; Jason Kokoszka; Jace Daniels; Laura Dickson; John Buckleton; Jo-anne Bright
• Date Published: March 2023
• Grant Number(s): 2020-DQ-BX-0022
• Agencies: NIJ-Sponsored
• Publication Type: Research (Applied/Empirical)

Annotation

This article presents research into utilizing compound likelihood ratios when analyzing forensic DNA mixtures.

Abstract

Simple propositions are defined as those with one POI and the remaining contributors unknown under H_p and all unknown contributors under H_a. Conditional propositions are defined as those with one POI, one or more assumed contributors, and the remaining contributors (if any) unknown under H_p, and the assumed contributor(s) and N unknown contributors under H_a. In this study, compound propositions are those with multiple POI and the remaining contributors unknown under H_p and all unknown contributors under Ha. The authors study the performance of these three proposition sets on thirty-two samples (two laboratories × four NOCs × four mixtures) consisting of four mixtures, each with N = 2, N = 3, N = 4, and N = 5 contributors using the probabilistic genotyping software, STRmix™. In this study, it was found that conditional propositions have a much higher ability to differentiate true from false donors than simple propositions. Compound propositions can misstate the weight of evidence given the propositions strongly in either direction. (Published Abstract Provided)