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Bayesian Analysis of DNA Profiling Data in Forensic Identification Applications
Author(s) -
Foreman Lindsey A.,
Smith Adrian F. M.,
Evett Ian W.
Publication year - 1997
Publication title -
journal of the royal statistical society: series a (statistics in society)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.103
H-Index - 84
eISSN - 1467-985X
pISSN - 0964-1998
DOI - 10.1111/j.1467-985x.1997.00074.x
Subject(s) - bayesian probability , profiling (computer programming) , forensic science , dna profiling , forensic identification , identification (biology) , computer science , population , crime scene , data science , statistics , econometrics , psychology , mathematics , artificial intelligence , criminology , biology , dna , demography , sociology , genetics , botany , operating system
The utilization of DNA evidence in cases of forensic identification has become widespread over the last few years. The strength of this evidence against an individual standing trial is typically presented in court in the form of a likelihood ratio (LR) or its reciprocal (the profile match probability). The value of this LR will vary according to the nature of the genetic relationship between the accused and other possible perpetrators of the crime in the population. This paper develops ideas and methods for analysing data and evaluating LRs when the evidence is based on short tandem repeat profiles, with special emphasis placed on a Bayesian approach. These are then applied in the context of a particular quadruplex profiling system used for routine case‐work by the UK Forensic Science Service.