Prospective crime mapping in operational context Final report

Time of day consistency?As noted above, a further question raised was whether burglaries that occur very close toeach other in space and time (within a few days) are committed at the same time of dayusually within the same police shift as each other? The fact that hotspots change according toshift (e.g. see Ratcliffe 2002) inclines one to that view, but a more direct test was sought. Anaffirmative set of results would suggest that a burglary not only confers risk for a particulargeography and duration, but also for a specific time of day (morning, afternoon or evening).To illustrate, consider that an offender might have a preference for certain activities during theday (see Rengert and Wasilchick, 2000). Consequently, he/she may visit certain locationsduring daytime hours. Whilst there, he/she may commit offences if the opportunity presentsitself. This rhythm of activity, if regular enough, means that an offender will be at certainplaces at certain times. If he/she chooses to commit crimes, and in particular near-repeats atthese locations, then one would expect to see some consistency in the time of day at whichburglaries are committed in those areas. Burglars would appear to work shifts.To examine this hypothesis, one year’s data (January-December 2004) were analysed for thepolice force area (N=8,968). Each crime was compared to every other and the number ofcrimes that occurred at different spatial and temporal intervals identified. In line with theauthors’ earlier work, the spatial intervals here used were multiples of 100m, and the temporalintervals one week periods. Next, all events were compared to see if they occurred during thesame police shift (7am to 3pm, 3pm to 10pm, or 10pm to 7am) and a contingency tablepopulated. Comparisons between events that occurred on the same day as each other wereexcluded from the analyses presented as their inclusion has the potential to inflate theconsistency observed 3 - as a crime series committed during one evening would naturally beconsistent in terms of the police shift during which the events occurred as well as where theyoccurred.To determine during which shift an event occurred, data concerned with the day and time ofeach burglary were analysed. Typically, most burglaries occur when a victim is away from theproperty. Accordingly, rather than recording a single time at which a crime may have takenplace, the police ask for a likely time window, expressed as the earliest time to the latest timethe burglary could have occurred. This was mentioned earlier as a qualification on theanalysis of crimes by shift. In the analysis that follows, the midpoint of these two times wasused as an indicator of the time of the event. Crimes were excluded from the analysis if thetime window (for the earliest and latest day and times) exceeded 15 hours. Follow-upanalyses used shorter intervals of four and eight hours, and revealed the same pattern ofresults.To determine whether the emergent patterns differed from what would be expected on thebasis of chance, if the time of day that near-repeat burglaries were committed were unrelated,Monte-Carlo simulation was used to generate a chance distribution. To do this, using apseudo-random number generator, each crime was randomly assigned the police shift for adifferent burglary (each shift was reassigned only once), and a new contingency tablederived. This was completed 999 times. If the observed results represent a statisticallysignificant pattern, then one would expect that for any space-time combination (e.g. eventsthat occurred within 100m and seven days of each other) the number of burglaries for whichthe shifts are concordant would be greater than the Monte-Carlo results for at least 95 percent of the simulations. This equates to a threshold of statistical significance at the five percent level. In this analysis, as so many comparisons were made, the more conservative oneper cent level of statistical significance was adopted.A subset of the results, shown as Figure 4.1, are presented as the ratio of the observednumber of burglary pairs for which the events occurred during the same time of day (shift),divided by the mean of the Monte-Carlo simulations. Thus, a value of one would indicate thatthe observed value was equal to that expected. Statistically significant results are highlightedwith exaggerated markers on the graph. The dotted line shows that for events which occurredbetween 1,000m of each other, the observed number of burglary pairs that occurred during3 Analyses which included such comparisons produced an identical pattern of results.39