Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2003-2-14
pubmed:abstractText
Quantitative measures of the importance of evidence such as the "likelihood ratio" have become increasingly popular in the courtroom. These measures have been used by expert witnesses formally to describe their certainty about a piece of evidence. These measures are commonly interpreted as the amount by which the evidence should revise the opinion of guilt, and thereby summarize the importance of a particular piece of evidence. Unlike DNA evidence, quantitative measures have not been widely used by forensic dentists to describe their certainty when testifying about bitemark evidence. There is, however, no inherent reason why they should not be used to evaluate bitemarks. The purpose of this paper is to describe the likelihood ratio as it might be applied to bitemark evidence. We use a simple bitemark example to define the likelihood ratio, its application, and interpretation. In particular we describe how the jury interprets the likelihood ratio from a Bayesian perspective when evaluating the impact of the evidence on the odds that the accused is guilty. We describe how the dentist would calculate the likelihood ratio based on frequentist interpretations. We also illustrate some of the limitations of the likelihood ratio, and show how those limitations apply to bitemark evidence. We conclude that the quality of bitemark evidence cannot be adequately summarized by the likelihood ratio, and argue that its application in this setting may be more misleading than helpful.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
D
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0258-414X
pubmed:author
pubmed:issnType
Print
pubmed:volume
20
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
31-7
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
Weighing evidence: quantitative measures of the importance of bitemark evidence.
pubmed:affiliation
Department of Preventive Medicine and Biometrics, University of Colorado Health Sciences Center, Denver, Colorado, USA.
pubmed:publicationType
Journal Article, Review