RETRACTED ARTICLE: Investigative advising: a job for Bayes
Tóm tắt
Bayesian approaches to police decision support offer an improvement upon more commonly used statistical approaches. Common approaches to case decision support often involve using frequencies from cases similar to the case under consideration to come to an isolated likelihood that a given suspect either a) committed the crime or b) has a given characteristic or set of characteristics. The Bayesian approach, in contrast, offers formally contextualized estimates and utilizes the formal logic desired by investigators. Bayes’ theorem incorporates the isolated likelihood as one element of a three-part equation, the other parts being 1) what was known generally about the variables in the case prior to the case occurring (the scientific-theoretical priors) and 2) the relevant base rate information that contextualizes the evidence obtained (the event context). These elements are precisely the domain of decision support specialists (investigative advisers), and the Bayesian paradigm is uniquely apt for combining them into contextualized estimates for decision support. By formally combining the relevant knowledge, context, and likelihood, Bayes’ theorem can improve the logic, accuracy, and relevance of decision support statements.
Tài liệu tham khảo
Alison L, Rainbow L (Eds): Professionalizing offender profiling: forensic and investigative psychology in practice. London: Routledge; 2011.
Alison L, Smith MD, Eastman O, Rainbow L: Toulmins philosophy of argument and its relevance to offender profiling.Psychol Crime Law 2003,9(2):173–183.
Allen JC, Goodwill AM, Watters K, Beauregard E: Base rates and Bayes’ theorem for decision support.Policing: An Int J Police Strateg Manage in press.
Almond L, Alison L, Porter L: An evaluation and comparison of claims made in behavioural investigative advice reports compiled by the National Policing Improvement Agency in the United Kingdom. In Professionalizing offender profiling: forensic and investigative psychology in practice. Edited by: Alison L, Rainbow L. London: Routledge; 2011:250–263.
Blair JP, Rossmo DK: Evidence in context: Bayes’ theorem and investigations.Police Q 2010, 13:123–135.
De Morgan A: An essay on probabilities and their application to life contingencies and insurance offices. London: Longman, Orme, Brown, Green, & Longmans; 1838.
Donaldson T, Wollert R: A mathematical proof and example that Bayes’s theorem is fundamental to actuarial estimates of sexual recidivism risk.Sex Abuse 2008,20(2):206–217.
Doren DM: Battling with Bayes: when statistical analyses just won’t do.Sex Offender Law Report 2006,7(4):49–50. 60–61
Dowden C, Bennell C, Bloomfield S: Advances in offender profiling: a systematic review of the profiling literature published over the past three decades.Journal of Police and Criminal Psychology 2007, 22:44–56.
Gill J: Bayesian methods, a social and behavioural sciences approach. 2nd edition. London: CRC Press; 2009.
McGrayne SB: The theory that would not die: how Bayes’ rule cracked the enigma code, hunted down Russian submarines, and emerged triumphant from two centuries of controversy. New York: Yale University Press; 2011.
Popper K: Objective knowledge: an evolutionary approach. London: Oxford University Press; 1972.
Rainbow L: The UK approach to the management of behavioural investigative advice. In Professionalizing offender profiling: forensic and investigative psychology in practice. Edited by: Alison L, Rainbow L. London: Routledge; 2011:5–17.
Rainbow L, Almond L, Alison L: BIA support to investigative decision making. In Professionalizing offender profiling: forensic and investigative psychology in practice. Edited by: Alison L, Rainbow L. London: Routledge; 2011:35–50.
Rossmo DK: Geographic profiling. New York: CRC Press; 2000.
Rossmo DK: Geographic profiling in serial rape investigations. In Practical aspects of rape investigation: a multidisciplinary approach. 4th edition. Edited by: Hazelwood RR, Burgess AW. Boca Raton: CRC Press; 2009:139–170.
Salo B, Sirén J, Corander J, Zappalà A, Bosco D, Mokros A, Santtila P: Using Bayes’ theorem in behavioural crime linking of serial homicide.Leg Criminol Psychol 2012. Advance online publication. doi:10.1111/j.2044–8333.2011.02043.x
Schneps L, Colmez C: Math on trial: how numbers get used and abused in the courtroom. New York: Basic Books; 2013.
Tartoni F, Aitken C, Garbolino P, Biedermann A: Bayesian networks and probabilistic inference in forensic science. New York: John Wiley & Sons, Ltd.; 2006.
Wells GL, Turtle JW: Eyewitness identification: the importance of lineup models.Psychol Bull 1986,99(3):320–329.
Wollert R: Poor diagnostic reliability, the null-Bayes logic model, and their implications for sexually violent predator evaluations.Psychology, Public Policy, and Law 2007,13(3):167–203.
Woodhams J, Bull R, Hollin C: Case linkage-identifying crimes committed by the same offender. In Kocsis (Ed.), Criminal profiling: International theory, research, and practice (pp. 117–133). Totowa, NJ: Humana Press Inc.; 2007.