title: Posterior distributions for likelihood ratios in forensic science.
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.
authors.affiliation: Department of Statistical Science, University College London, Gower Street, London WC1E 6BT, United Kingdom. Electronic address: ardo.vandenhout@ucl.ac.uk.
authors.forename: Ardo
authors.initials: A
authors.lastname: van den Hout
authors.affiliation: Netherlands Forensic Institute, Laan van Ypenburg 6, The Hague, The Netherlands.
authors.forename: Ivo
authors.initials: I
authors.lastname: Alberink
mesh_terms: D001827:Body Height; D044707:Forensic Sciences; D006801:Humans; D016013:Likelihood Functions
keywords: Bayes factor; Bayesian inference; Body height estimation; Likelihood ratio; Posterior likelihood ratios; Precision; Reliability