The offence risk posed by individuals who are arrested, but where subsequently no charge or caution is administered, has been used in the UK as an argument for justifying the retention of such individuals' DNA and identification profiles. Here we consider the UK Home Office arrest-to-arrest data analysis, and find it to have limited use in indicating risk of future offence. In doing so, we consider the appropriateness of the statistical methodology employed and the implicit assumptions necessary for making such inference concerning the re-arrest risk of a further individual. Additionally, we offer an alternative model that would provide an equally accurate fit to the data, but which would appear to have sounder theoretical justification and result in vastly different conclusions for policy development. Finally, we consider the implications of using such statistical inference in formulating national policy, and highlight a number of sociological factors that could be taken into account so as to enhance the validity of any future analysis.
Keywords: probabilistic causality; statistical inference; reliability modelling; DNA profiling
Biography: Dr Brett Houlding is a Research Fellow within the Science Foundation Ireland funded Statistical Methods for ICT Applications (STATICA) project at Trinity College Dublin. He received a Masters Degree in Mathematical Sciences in 2004 from Durham University (UK) before completing a doctoral thesis concerning sequential decision making with uncertain preferences in 2008 from the same instution. His research interests are primarily focused on the foundations of statistics and normative Bayesian statistical decision theory, though he has also worked in reliability analysis, applications of imprecise probability theory, estimating number of unknown species, and statistical concerns arising out of court scenarios.