Recent advances in police open data initiatives across the United States allow for analyses of datasets in criminology and policing across a variety of spatial scales. However, existing statistical methods often do not allow for the utilization of the original spatial granularity or event-level information present in these complex datasets. My dissertation addresses gaps in spatial statistical methodology for analyzing crime and policing data. In particular I (1) propose a new approach to analyze areal crime data through the use of both spatial and social dependence between communities, (2) develop a two-stage approach to study marked point process data with flexible relationships between the location-determination and the mark-determination stages of the point process model, (3) adapt a new shared component model for point process data that allows for flexible characterization of shared spatial patterns between point patterns, and unique drivers of each point process, and (4) explore a method for privatizing data that preserves its statistical utility. (Publisher abstract provided.)
Advances in Spatial Models for Urban Crime
NCJ Number
310679
Date Published
August 2022
Length
192 pages
Abstract
Date Published: August 1, 2022