Crimes between 2000 and 2013 were used to identify different trajectory groups at street segments and intersections. Zero-inflated Poisson regression models were used to identify the trajectories. Pin maps, Ripley's K and neighbor transition matrices were used to show the spatial patterning of the trajectory groups. The trajectory solution with eight classes was selected, based on several model selection criteria. The trajectory of each of those groups followed the overall citywide decline, and were only separated by the mean level of crime. Spatial analysis shows that higher crime trajectory groups were more likely to be nearby one another, potentially suggesting a diffusion process. This study adds additional support to others that have found tight coupling of crime at micro-places. The clustering of trajectories identified a set of street units that disproportionately contributed to the total level of crime citywide in Albany, consistent with previous research; however, the temporal trends over time in Albany differed from those exhibited in previous work in Seattle, but were consistent with patterns in Vancouver. (Publisher abstract modified)
Replicating Group-Based Trajectory Models of Crime at Micro-Places in Albany, NY
NCJ Number
252448
Journal
Journal of Quantitative Criminology 32(4): 589-612 Volume: 32 Issue: 4 Dated: December 2016 Pages: 589-612
Date Published
December 2016
Length
24 pages
Annotation
In replicating the general approach of group-based trajectory modelling of crimes at micro-places originally taken by Weisburd et al. (Criminology 42(2):283-322, 2004) and replicated by Curman et al. (J Quant Criminol 31(1):127-147, 2014), the current study examined patterns in a city of a different character (Albany, NY) than those previously examined (Seattle and Vancouver), and thus contribute to the generalizability of previous findings.
Abstract