Identifying and modelling the drivers of stutter in forensic DNA profiles

• NCJ Number: 307102
• Journal: Australian Journal of Forensic Sciences Volume: 46 Issue: 2 Dated: 2014 Pages: 194-203
• Author(s): Hannah Kelly; Jo-Anne Bright; John S. Buckleton; James M. Curran
• Date Published: 2014
• Length: 10 pages
• Grant Number(s): 2011-DN-BX-K541
• Sponsoring Agency: National Institute of Justice (NIJ)
• Corporate Author: University of Washington
• Publication Format: Article
• Publication Type: Research (Applied/Empirical)
• Language: English
• Country: United States of America

Annotation

The goals of the research being reported in this paper were to produce models for forensic casework use with the intention of understanding the causes of stutter and the variability in stutter product, in order to contribute to the understanding of the interpretation of mixed source samples as well as the process of determining if a sample is mixed source at all.

Abstract

This paper investigates the variables that could affect the stutter ratio (SR). Bayesian modelling techniques are used to model the distribution of the SR using the parameters identified: the locus and the longest uninterrupted sequence (LUS). The final model gives an expected estimate for the SR as well as the distribution about this estimate. (Publisher Abstract Provided)