Prospective crime mapping in operational context Final report

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Table 2.6: Monte-Carlo results for Wellingborough (values in bold are statisticallysignificant, N=1350)MONTHS1 2 3 4 5 6100 1.57 0.97 0.77 0.82 1.00 0.72200 1.35 1.01 0.85 0.77 0.91 0.86300 1.26 0.96 0.90 0.81 0.90 0.93400 1.21 0.99 0.96 0.91 0.91 0.92500 1.16 1.03 0.93 1.00 0.94 0.95600 1.10 1.03 1.00 0.93 0.92 0.86700 1.01 1.05 0.98 0.98 0.95 0.91800 1.08 0.98 1.03 1.02 0.99 0.89900 1.01 0.98 0.95 0.96 0.99 0.941000 0.98 1.01 1.04 0.98 0.92 1.05These findings illustrate a problem with analyses where a certain level of aggregation isemployed. This is known as Simpson’s paradox (Simpson, 1969). This occurs where dataaggregated up to a fairly large unit of analysis such as one month, mask subtle trendsapparent where data disaggregated to a finer level of resolution (such as one week) are used.In this case, it would appear from the analysis shown in Table 2.7 that the risk to houses up to600m from victimised homes endures for around six to seven weeks rather than four. In anyevent, it is apparent that the risks are consistently greater within the first month.Table 2.7: Weekly Knox ratios for Wellingborough (values in bold are statisticallysignificant according to the residual scores (not shown), N=1350)WEEKS1 2 3 4 5 6 7 8 9 10 11 12100 1.82 1.78 1.76 1.67 1.53 1.39 1.22 1.06 0.97 0.87 0.78 0.76200 1.64 1.56 1.46 1.39 1.27 1.18 1.09 1.03 1.00 0.96 0.89 0.86300 1.52 1.43 1.37 1.29 1.20 1.12 1.04 1.00 0.94 0.91 0.88 0.88400 1.39 1.28 1.23 1.21 1.15 1.09 1.04 0.99 0.95 0.94 0.96 0.95500 1.27 1.23 1.19 1.18 1.13 1.11 1.06 1.04 1.01 0.98 0.97 0.95600 1.11 1.08 1.09 1.11 1.08 1.08 1.06 1.05 1.03 1.03 1.02 1.01700 1.02 1.01 1.02 1.00 1.02 1.04 1.06 1.06 1.04 1.01 1.00 1.00800 1.16 1.08 1.10 1.07 1.05 1.04 1.02 1.00 0.99 1.00 1.00 1.03900 1.04 1.03 1.01 1.01 1.01 0.99 0.98 0.97 0.98 0.98 0.98 0.981000 1.00 1.01 1.01 0.99 0.97 0.97 0.96 1.00 1.01 1.01 1.04 1.04Ashfield Police SectorFor Ashfield, the data cover the period January-December 2004 and a total of 1,012 burglaryevents. The results of the monthly Knox and Monte-Carlo analyses are shown as Tables 2.8and 2.9 respectively.9
Table 2.8: Knox ratios for Ashfield (values in bold are statistically significantaccording to the residual scores (not shown), N=1012)MONTHS1 2 3 4 5 6100 1.19 0.96 1.04 1.04 0.96 0.79200 1.17 0.99 0.94 0.97 1.00 0.91300 1.18 0.96 0.99 0.99 0.95 1.00400 1.11 0.96 0.96 1.11 0.94 1.01500 1.02 1.03 0.99 1.05 0.96 1.00600 1.09 1.04 1.01 1.07 0.97 0.98700 1.12 0.96 1.07 1.05 0.91 0.89800 0.99 1.01 1.02 0.98 0.96 1.06900 0.96 0.96 1.08 0.96 1.05 0.981000 0.97 1.02 1.02 1.01 1.06 0.92The results are again very consistent. Both analyses suggest that the risk of burglarycommunicates over a distance of up to 700m and endures for one month. Interestingly, therisk communicated to houses within 401-500m appears to be non-significant. This is difficultto explain. It could be an expression of the spatial distribution of targets across the area, orperhaps suggests the existence of a natural boundary that generates this pattern bydiscouraging some offenders from travelling from one area to a second nearby. Moreresearch would be required to understand this effect. Nevertheless, the results clearlydemonstrate that the risk of burglary is communicable.Table 2.9: Monte-Carlo results for Ashfield (values in bold are statistically significant,N=1012)MONTHS1 2 3 4 5 6100 1.18 0.96 1.03 1.05 0.96 0.80200 1.17 0.98 0.95 0.97 1.00 0.92300 1.17 0.97 0.98 0.99 0.94 1.01400 1.11 0.95 0.97 1.11 0.95 1.00500 1.02 1.03 0.98 1.05 0.96 0.98600 1.08 1.04 1.01 1.07 0.98 0.97700 1.12 0.96 1.07 1.06 0.90 0.90800 0.99 1.00 1.03 0.97 0.96 1.06900 0.96 0.96 1.08 0.94 1.07 0.981000 0.97 1.01 1.03 1.02 1.07 0.92As before, an additional Knox analysis was conducted to examine the temporal trend in moredetail. The results, shown as Table 2.10, suggest a similar pattern of risk, but additionallysuggest that houses between 401-500m of burgled homes are at an elevated (albeitmarginally non-significant) risk of victimisation for up to two weeks after an initial burglary.Thus, this suggests that the risk of victimisation is, in general, communicable up to 700m, butfor slightly different time periods.10
Page 2 and 3: 1. UCL JILL DANDO INSTITUTE OF CRIM
Page 4 and 5: ContentsAcknowledgementsExecutive s
Page 6 and 7: 2.5 Illustration of a simple neares
Page 8 and 9: Project outcomesPatterns of burglar
Page 10 and 11: those that involved collaboration w
Page 12 and 13: 1. IntroductionThis report represen
Page 14 and 15: optimally calibrated system, the go
Page 16 and 17: e ij = n .j x n i.nWhere, e ij is t
Page 18 and 19: Table 2.2: Knox ratios for Mansfiel
Page 22 and 23: Table 2.10: Weekly Knox ratios for
Page 24 and 25: Table 2.14: Monte-Carlo results for
Page 26 and 27: Figure 2.1: The five policing areas
Page 28 and 29: The results for area 5 again demons
Page 30 and 31: The bandwidth used to generate the
Page 32: a densely populated urban area this
Page 35 and 36: Table 2.24: Average number of crime
Page 37 and 38: Patrolling efficiencyAs discussed e
Page 39 and 40: 3. Tactical options and selecting a
Page 41 and 42: Selecting a pilot siteThe decision
Page 43 and 44: Table 3.2: Tactical options matrixT
Page 45 and 46: Type ofinterventionStudyUse ofintel
Page 47 and 48: Other potential tactical optionsAt
Page 49 and 50: 4. System development and evolution
Page 51 and 52: the same time of day as each other
Page 53 and 54: unfortunately, implementation or us
Page 55 and 56: any tactical options were employed
Page 57 and 58: the end of the pilot. In addition t
Page 59 and 60: Figure 5.1: Promap dissemination pr
Page 61 and 62: the busy schedule of the new Divisi
Page 63 and 64: Tactical deliveryCommand Team daily
Page 65 and 66: Table 5.3: Number of respondents wh
Page 67 and 68: permitted, up to four plain clothed
Page 69 and 70: observation made by those who used
Page 71 and 72:
A simple time-series analysis (see
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Two approaches were used to compute
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Figure 6.3: Changes in the proporti
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Figure 6.5: Changes in the proporti
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With respect to implementation real
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ReferencesAggresti, A. (1996) An In
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Johnson, S.D., Summers, L., and Pea
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Appendix 1. The information technol
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Figure A1.2: Stand-alone applicatio
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Recommendations that may be realise
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Section 1: knowledge and understand
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Extra Comments (please outline any
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In relation to the evaluation of in
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Time-series analysisFor the purpose
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Figure A3.1: Changes in the spatial
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Figure A3.2: Lorenz curves showing
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To recapitulate and elaborate, the
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Concluding comments on methodThe te
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Figure A5.2: An enlargement of the
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Figure A5.6: Prospective map magnif
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Produced by the Research Developmen
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Prospective crime mapping in operational context Final report

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