Literature DB >> 27702459

Posterior distributions for likelihood ratios in forensic science.

Ardo van den Hout1, Ivo Alberink2.   

Abstract

Evaluation of evidence in forensic science is discussed using posterior distributions for likelihood ratios. Instead of eliminating the uncertainty by integrating (Bayes factor) or by conditioning on parameter values, uncertainty in the likelihood ratio is retained by parameter uncertainty derived from posterior distributions. A posterior distribution for a likelihood ratio can be summarised by the median and credible intervals. Using the posterior mean of the distribution is not recommended. An analysis of forensic data for body height estimation is undertaken. The posterior likelihood approach has been criticised both theoretically and with respect to applicability. This paper addresses the latter and illustrates an interesting application area.
Copyright © 2016 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

Keywords:  Bayes factor; Bayesian inference; Body height estimation; Likelihood ratio; Posterior likelihood ratios; Precision; Reliability

Mesh:

Year:  2016        PMID: 27702459     DOI: 10.1016/j.scijus.2016.06.011

Source DB:  PubMed          Journal:  Sci Justice        ISSN: 1355-0306            Impact factor:   2.124


  2 in total

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Authors:  Peter Gill; Corina Benschop; John Buckleton; Øyvind Bleka; Duncan Taylor
Journal:  Genes (Basel)       Date:  2021-09-30       Impact factor: 4.096

2.  The Limits of Bayesian Thinking in Court.

Authors:  Ronald Meester
Journal:  Top Cogn Sci       Date:  2019-10-31
  2 in total

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