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dc.contributor.authorDuggan, Conor
dc.date.accessioned2017-09-20T16:06:18Z
dc.date.available2017-09-20T16:06:18Z
dc.date.issued2017
dc.identifier.citationDuggan, C. & Jones, R. (2017). Managing uncertainty in the clinical prediction of risk of harm: Bringing a Bayesian approach to forensic mental health. Criminal Behaviour and Mental Health, 27 (1), pp.1-7.
dc.identifier.other10.1002/cbm.2031
dc.identifier.urihttp://hdl.handle.net/20.500.12904/14284
dc.description.abstractPredicting the likelihood of harm posed by mentally disordered offenders remains controversial. It is proposed that a Bayesian approach may help quantify the uncertainty surrounding such prediction. An example of this approach quantifying the risk of breast cancer in the event of a positive mammogram is provided. Copyright (c) 2017 John Wiley & Sons, Ltd.
dc.description.urihttp://onlinelibrary.wiley.com/doi/10.1002/cbm.2031/abstract;jsessionid=BB9E6E40DBFE9BE5134A3BAAD5E6E4D1.f03t01
dc.subjectCriminals
dc.subjectMental disorders
dc.titleManaging uncertainty in the clinical prediction of risk of harm: Bringing a Bayesian approach to forensic mental health
dc.typeArticle
html.description.abstractPredicting the likelihood of harm posed by mentally disordered offenders remains controversial. It is proposed that a Bayesian approach may help quantify the uncertainty surrounding such prediction. An example of this approach quantifying the risk of breast cancer in the event of a positive mammogram is provided. Copyright (c) 2017 John Wiley & Sons, Ltd.


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