A Multi-Jurisdictional Test of Risk Terrain Modeling and a Place-Based Evaluation of Environmental Risk-Based Patrol Deployment Strategies, 6 U.S. States, 2012-2014 (ICPSR 36369)

Version Date: May 29, 2018

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Principal Investigator(s):
Leslie W. Kennedy, Rutgers University. School of Criminal Justice; Joel M. Caplan, Rutgers University. School of Criminal Justice; Eric L. Piza, John Jay College of Criminal Justice

https://doi.org/10.3886/ICPSR36369.v1

Version V1

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Summary

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.

The study used a place-based method of evaluation and spatial units of analysis to measure the extent to which allocating police patrols to high-risk areas effected the frequency and spatial distribution of new crime events in 5 U.S. cities. High-risk areas were defined using risk terrain modeling methods. Risk terrain modeling, or RTM, is a geospatial method of operationalizing the spatial influence of risk factors to common geographic units.

The collection contains 333 shape files, 8 SPSS files, and 9 Excel files. The shape files include both city level risk factor locations and crime data from police departments. SPSS and Excel files contain output from GIS data used for analysis.

Citation

Kennedy, Leslie W., Caplan, Joel M., and Piza, Eric L. A Multi-Jurisdictional Test of Risk Terrain Modeling and a Place-Based Evaluation of Environmental Risk-Based Patrol Deployment Strategies, 6 U.S. States, 2012-2014. Inter-university Consortium for Political and Social Research [distributor], 2018-05-29. https://doi.org/10.3886/ICPSR36369.v1

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Funding

United States Department of Justice. Office of Justice Programs. National Institute of Justice (2012-IJ-CX-0038)

Subject Terms

Geographic Coverage

Smallest Geographic Unit

Census tract

Restrictions

Access to these data is restricted. Users interested in obtaining these data must complete a Restricted Data Use Agreement, specify the reason for the request, and obtain IRB approval or notice of exemption for their research.

Distributor(s)

Inter-university Consortium for Political and Social Research
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Time Period(s)

2012 -- 2014

Date of Collection

2012 (Risk Factor Data), 2013 -- 2014 (Intervention Crime Data from Police Departments)

Data Collection Notes

  1. These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.

  2. Data files sourced from InfoGroup are not included in the deposit.

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Study Purpose

A place-based method of evaluation and spatial units of analysis were used to measure the extent to which allocating police resources to high-rick areas, derived from risk terrain modeling (RTM), affects the frequency and spatial distribution of new crime events. This quasi-experimental project had two primary goals: 1) to replicate and validate RTM in multiple jurisdictions and across many different crime types; and 2) to evaluate intervention strategies targeted at high-risk micro-level environments across 5 cities: Chicago, IL; Colorado Springs, CO; Glendale, AZ; Kansas City, MO; and Newark, NJ.

Study Design

In completing the risk terrain models (RTM), the RTMDx Utility, developed by the Rutgers Center on Public Security, was used. The Utility applied a precise set of statistical tests to evaluate the relative importance of spatial factors in influencing crime outcomes. The Utility begins by building an elastic net penalized regression model assuming a Poisson distribution of events. It does this using cross-validation. The Utility then further simplifies the model in subsequent steps via a bidirectional step wise regression process (Poisson and negative binomial) and measures the Bayesian Information Criteria (BIC) score. The best model with the lowest BIC score between Poisson and negative binomial distributions is selected.

RTMDx outputs are tabular and cartographic; for each significant risk factor, tabular outputs include a relative risk value (RRV), which is the exponentiated factor coefficient (i.e., relative weight), and the optimal operationalization and distal extent of spatial influence. A risk terrain map is also produced to show highest risk places throughout the study area.

Following the RTM analysis in each city, each Police Department developed an intervention strategy that targeted the spatial influences of select significant risk factors. The Police Department also worked with the research team in the selection of target areas for the intervention. In evaluating the intervention, statistical comparisons were made to equivalent control areas locally within each city. Control areas were matched to treatment areas through Propensity Score Matching.

Sample

A census of all elements of each city was used for this project. No sampling was done for this project.

Time Method

Longitudinal, Longitudinal: Cohort / Event-based

Universe

City-level crime incidents

Unit(s) of Observation

Metropolitan Area

Data Source

Chicago Police Department (Chicago, IL)

Glendale Police Department (Glendale, AZ)

Newark Police Department (Newark, NJ)

Colorado Springs Police Department (Colorado Springs, CO)

Arlington Police Department (Arlington, TX)

Kansas City Police Department (Kansas City, MO)

Data Type(s)

Description of Variables

Variables used in analysis were X and Y coordinates of risk factor locations including foreclosures, parks, bars, and liquor stores as well as coordinate locations of city level crime occurrences, including car theft, shootings, aggravated violence, and drug related crime.

Response Rates

Not Applicable

Presence of Common Scales

None

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Original Release Date

2018-05-29

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Weight

None

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Notes

  • These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.

  • The public-use data files in this collection are available for access by the general public. Access does not require affiliation with an ICPSR member institution.

  • One or more files in this data collection have special restrictions. Restricted data files are not available for direct download from the website; click on the Restricted Data button to learn more.