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Bayesian journey‐to‐crime modelling of juvenile and adult offenders by gender in Manchester
Author(s) -
Levine Ned,
Lee Patsy
Publication year - 2009
Publication title -
journal of investigative psychology and offender profiling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.479
H-Index - 22
eISSN - 1544-4767
pISSN - 1544-4759
DOI - 10.1002/jip.110
Subject(s) - bayesian probability , juvenile delinquency , profiling (computer programming) , offender profiling , psychology , predictability , juvenile , criminology , bayesian inference , computer science , statistics , artificial intelligence , mathematics , bayesian network , biology , genetics , operating system
This study tested the Bayesian journey‐to‐crime (JTC) model by gender and age for serial offenders from Manchester, England. The data were 4056 crimes committed by 171 serial offenders between 2003 and 2006. The data were subdivided by gender and age group to examine whether accuracy and precision varied by these subgroups. In general, the centre of minimum distance was found to be the most accurate measure, but the Bayesian risk and product measures were found to be the most precise measurements. The traditional ‘distance decay’ type of JTC function did not produce estimates that are as accurate nor as precise as the Bayesian approach. Tests were conducted on whether specific gender and age group JTC functions and origin–destination matrices improved predictability. With the exception of juvenile male offenders, the general functions were more accurate and precise. In terms of building an accurate and precise geographical profiling methodology, the results point to the need to include information on the likely predisposition of neighbourhoods to produce offenders as well as information on the crime opportunities available to offenders. Copyright © 2009 John Wiley & Sons, Ltd.